[{"_id": {"$oid": "69d4eb12b877594bc5718d76"}, "test_id": "T0557", "benchmark": "business_letters", "date": "2026-03-31", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "ministral-8b-2512", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"null\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"null\"]}}", "model": "ministral-8b-2512", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 415, "total_tokens": 1000, "input_cost_usd": 8.775e-05, "output_cost_usd": 6.225e-05, "estimated_cost_usd": 0.00015000000000000001}, "duration": 2.413496732711792, "timestamp": "2026-03-31T11:40:12.334278", "parsed": {"$defs": {"Metadata": {"properties": {"receiver_persons": [{"items": {"type": "string"}, "type": "array"}, {"type": "null"}], "title": "Receiver Persons"}}, "required": ["letter_title", "send_date", "sender_persons", "receiver_persons"], "title": "Metadata", "type": "object"}, "properties": {"metadata": {"$ref": "#/$defs/Metadata"}}, "required": ["metadata"], "title": "Document", "type": "object", "$schema": "http://json-schema.org/draft-07/schema#", "metadata": {"letter_title": ["null"], "send_date": ["null"], "sender_persons": ["null"], "receiver_persons": ["null"], "document_number": "letter29"}}, "conversation_id": "64a4fcf1-b5a0-4a74-b464-bbffedda492b", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"06ad7c5b3c7f4c7baf660ceaac0d703a\",\"object\":\"chat.completion\",\"model\":\"ministral-8b-2512\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":415,\"total_tokens\":1000,\"prompt_tokens_details\":{\"cached_tokens\":548}},\"created\":1774950010,\"choices\":[{\"index\":0,\"message\":{\"role\":\"assistant\",\"content\":\"{\\n \\\"$defs\\\": {\\n \\\"Metadata\\\": {\\n \\\"properties\\\": {\\n \\\"letter_title\\\": [\\n {\\n \\\"items\\\": {\\n \\\"type\\\": \\\"string\\\"\\n },\\n \\\"type\\\": \\\"array\\\"\\n },\\n {\\n \\\"type\\\": \\\"null\\\"\\n }\\n ],\\n \\\"title\\\": \\\"Letter Title\\\"\\n },\\n \\\"properties\\\": {\\n \\\"send_date\\\": [\\n {\\n \\\"items\\\": {\\n \\\"type\\\": \\\"string\\\"\\n },\\n \\\"type\\\": \\\"array\\\"\\n },\\n {\\n \\\"type\\\": \\\"null\\\"\\n }\\n ],\\n \\\"title\\\": \\\"Send Date\\\"\\n },\\n \\\"properties\\\": {\\n \\\"sender_persons\\\": [\\n {\\n \\\"items\\\": {\\n \\\"type\\\": \\\"string\\\"\\n },\\n \\\"type\\\": \\\"array\\\"\\n },\\n {\\n \\\"type\\\": \\\"null\\\"\\n }\\n ],\\n \\\"title\\\": \\\"Sender Persons\\\"\\n },\\n \\\"properties\\\": {\\n \\\"receiver_persons\\\": [\\n {\\n \\\"items\\\": {\\n \\\"type\\\": \\\"string\\\"\\n },\\n \\\"type\\\": \\\"array\\\"\\n },\\n {\\n \\\"type\\\": \\\"null\\\"\\n }\\n ],\\n \\\"title\\\": \\\"Receiver Persons\\\"\\n }\\n },\\n \\\"required\\\": [\\n \\\"letter_title\\\",\\n \\\"send_date\\\",\\n \\\"sender_persons\\\",\\n \\\"receiver_persons\\\"\\n ],\\n \\\"title\\\": \\\"Metadata\\\",\\n \\\"type\\\": \\\"object\\\"\\n },\\n \\\"properties\\\": {\\n \\\"metadata\\\": {\\n \\\"$ref\\\": \\\"#/$defs/Metadata\\\"\\n }\\n },\\n \\\"required\\\": [\\n \\\"metadata\\\"\\n ],\\n \\\"title\\\": \\\"Document\\\",\\n \\\"type\\\": \\\"object\\\",\\n \\\"$schema\\\": \\\"http://json-schema.org/draft-07/schema#\\\",\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [\\\"null\\\"],\\n \\\"send_date\\\": [\\\"null\\\"],\\n \\\"sender_persons\\\": [\\\"null\\\"],\\n \\\"receiver_persons\\\": [\\\"null\\\"]\\n }\\n}\",\"tool_calls\":null,\"prefix\":false},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 585, "total_output_tokens": 415, "total_tokens": 1000, "input_cost_usd": 8.775e-05, "output_cost_usd": 6.225e-05, "total_cost_usd": 0.00015000000000000001}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718d7b"}, "test_id": "T0556", "benchmark": "business_letters", "date": "2026-03-31", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "ministral-8b-2512", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"null\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"null\"]}}", "model": "ministral-8b-2512", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 407, "total_tokens": 992, "input_cost_usd": 8.775e-05, "output_cost_usd": 6.105e-05, "estimated_cost_usd": 0.0001488}, "duration": 2.836698293685913, "timestamp": "2026-03-31T11:40:05.900863", "parsed": {"$defs": {"Metadata": {"properties": {"letter_title": {"anyOf": [{"items": {"type": "string"}, "type": "array"}, {"type": "null"}], "title": "Letter Title"}, "send_date": {"anyOf": [{"items": {"type": "string"}, "type": "array"}, {"type": "null"}], "title": "Send Date"}, "sender_persons": {"anyOf": [{"items": {"type": "string"}, "type": "array"}, {"type": "null"}], "title": "Sender Persons"}, "receiver_persons": {"anyOf": [{"items": {"type": "string"}, "type": "array"}, {"type": "null"}], "title": "Receiver Persons"}}, "required": ["letter_title", "send_date", "sender_persons", "receiver_persons"], "title": "Metadata", "type": "object"}}, "properties": {"metadata": {"$ref": "#/$defs/Metadata"}}, "required": ["metadata"], "title": "Document", "type": "object", "metadata": {"letter_title": ["null"], "send_date": ["null"], "sender_persons": ["null"], "receiver_persons": ["null"], "document_number": "letter12"}}, "conversation_id": "c083bcca-b519-4b9a-bd0d-199e5a2125ce", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"b81e3e0c9a0742c089f1399d9a638cb9\",\"object\":\"chat.completion\",\"model\":\"ministral-8b-2512\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":407,\"total_tokens\":992,\"prompt_tokens_details\":{\"cached_tokens\":0}},\"created\":1774950003,\"choices\":[{\"index\":0,\"message\":{\"role\":\"assistant\",\"content\":\"{\\n \\\"$defs\\\": {\\n \\\"Metadata\\\": {\\n \\\"properties\\\": {\\n \\\"letter_title\\\": {\\n \\\"anyOf\\\": [\\n {\\n \\\"items\\\": {\\n \\\"type\\\": \\\"string\\\"\\n },\\n \\\"type\\\": \\\"array\\\"\\n },\\n {\\n \\\"type\\\": \\\"null\\\"\\n }\\n ],\\n \\\"title\\\": \\\"Letter Title\\\"\\n },\\n \\\"send_date\\\": {\\n \\\"anyOf\\\": [\\n {\\n \\\"items\\\": {\\n \\\"type\\\": \\\"string\\\"\\n },\\n \\\"type\\\": \\\"array\\\"\\n },\\n {\\n \\\"type\\\": \\\"null\\\"\\n }\\n ],\\n \\\"title\\\": \\\"Send Date\\\"\\n },\\n \\\"sender_persons\\\": {\\n \\\"anyOf\\\": [\\n {\\n \\\"items\\\": {\\n \\\"type\\\": \\\"string\\\"\\n },\\n \\\"type\\\": \\\"array\\\"\\n },\\n {\\n \\\"type\\\": \\\"null\\\"\\n }\\n ],\\n \\\"title\\\": \\\"Sender Persons\\\"\\n },\\n \\\"receiver_persons\\\": {\\n \\\"anyOf\\\": [\\n {\\n \\\"items\\\": {\\n \\\"type\\\": \\\"string\\\"\\n },\\n \\\"type\\\": \\\"array\\\"\\n },\\n {\\n \\\"type\\\": \\\"null\\\"\\n }\\n ],\\n \\\"title\\\": \\\"Receiver Persons\\\"\\n }\\n },\\n \\\"required\\\": [\\n \\\"letter_title\\\",\\n \\\"send_date\\\",\\n \\\"sender_persons\\\",\\n \\\"receiver_persons\\\"\\n ],\\n \\\"title\\\": \\\"Metadata\\\",\\n \\\"type\\\": \\\"object\\\"\\n }\\n },\\n \\\"properties\\\": {\\n \\\"metadata\\\": {\\n \\\"$ref\\\": \\\"#/$defs/Metadata\\\"\\n }\\n },\\n \\\"required\\\": [\\n \\\"metadata\\\"\\n ],\\n \\\"title\\\": \\\"Document\\\",\\n \\\"type\\\": \\\"object\\\",\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [\\\"null\\\"],\\n \\\"send_date\\\": [\\\"null\\\"],\\n \\\"sender_persons\\\": [\\\"null\\\"],\\n \\\"receiver_persons\\\": [\\\"null\\\"]\\n }\\n}\",\"tool_calls\":null,\"prefix\":false},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 585, "total_output_tokens": 407, "total_tokens": 992, "input_cost_usd": 8.775e-05, "output_cost_usd": 6.105e-05, "total_cost_usd": 0.0001488}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718d45"}, "test_id": "T0867", "benchmark": "business_letters", "date": "2026-03-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "alibaba", "model": "qwen3.5-397b-a17b", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"base_url\": \"https://ws-wkjpbv6ov7sqlgqe.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-07-13\"],\"letter_title\":[\"Betr. \\\"ALBATROS\\\"\"],\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Elektrizit\u00e4tswerk, Basel\"]}}", "model": "qwen3.5-397b-a17b", "provider": "alibaba", "finish_reason": "stop", "usage": {"input_tokens": 3108, "output_tokens": 104, "total_tokens": 3212, "input_cost_usd": 0.0018648, "output_cost_usd": 0.0003744, "estimated_cost_usd": 0.0022392000000000002}, "duration": 7.996857166290283, "timestamp": "2026-03-25T10:18:32.698138", "parsed": {"metadata": {"send_date": ["1926-07-13"], "letter_title": ["Betr. \"ALBATROS\""], "sender_persons": ["Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["Elektrizit\u00e4tswerk, Basel"], "document_number": "letter10"}}, "conversation_id": "9dab9a33-1c8d-45a3-ac2e-e6b81c1c3d63", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-e9f77e8d-80de-9bc5-b8df-bf601d94bb5b\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1926-07-13\\\"\\n ],\\n \\\"letter_title\\\": [\\n \\\"Betr. \\\\\\\"ALBATROS\\\\\\\"\\\"\\n ],\\n \\\"sender_persons\\\": [\\n \\\"Basler Personenschiffahrtsgesellschaft\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Elektrizit\u00e4tswerk, Basel\\\"\\n ]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"reasoning_content\":\"\"}}],\"created\":1774430313,\"model\":\"qwen3.5-397b-a17b\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":104,\"prompt_tokens\":3108,\"total_tokens\":3212,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":null,\"rejected_prediction_tokens\":null,\"text_tokens\":104},\"prompt_tokens_details\":{\"audio_tokens\":null,\"cached_tokens\":null,\"image_tokens\":2522,\"text_tokens\":586}}}"}, "scoring": {"f1_macro": 0.58, "f1_micro": 0.58, "cost_summary": {"total_input_tokens": 280558, "total_output_tokens": 5290, "total_tokens": 285848, "input_cost_usd": 0.16833480000000003, "output_cost_usd": 0.01904400000000001, "total_cost_usd": 0.18737879999999998}}, "normalized_score": 57.99999999999999}, {"_id": {"$oid": "69d4eb12b877594bc5718d68"}, "test_id": "T0880", "benchmark": "business_letters", "date": "2026-03-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "alibaba", "model": "qwen3.5-flash-2026-02-23", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"base_url\": \"https://ws-wkjpbv6ov7sqlgqe.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\n \"metadata\": {\n \"send_date\": [\n \"1928-04-04\"\n ],\n \"letter_title\": [\n null\n ],\n \"sender_persons\": [\n \"Basler Personenschifffahrtsgesellschaft\"\n ],\n \"receiver_persons\": [\n null\n ]\n }\n}", "model": "qwen3.5-flash-2026-02-23", "provider": "alibaba", "finish_reason": "stop", "usage": {"input_tokens": 5630, "output_tokens": 89, "total_tokens": 5719, "input_cost_usd": 0.000563, "output_cost_usd": 3.56e-05, "estimated_cost_usd": 0.0005986}, "duration": 6.547292709350586, "timestamp": "2026-03-25T10:18:34.357717", "parsed": {"metadata": {"send_date": ["1928-04-04"], "letter_title": [null], "sender_persons": ["Basler Personenschifffahrtsgesellschaft"], "receiver_persons": [null], "document_number": "letter24"}}, "conversation_id": "f2283608-c8f9-45e2-8205-609081d37a08", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-a09b3fe1-e22e-96a9-bc99-9d8c06751e7d\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1928-04-04\\\"\\n ],\\n \\\"letter_title\\\": [\\n null\\n ],\\n \\\"sender_persons\\\": [\\n \\\"Basler Personenschifffahrtsgesellschaft\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n null\\n ]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"reasoning_content\":\"\"}}],\"created\":1774430314,\"model\":\"qwen3.5-flash-2026-02-23\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":89,\"prompt_tokens\":5630,\"total_tokens\":5719,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":null,\"rejected_prediction_tokens\":null,\"text_tokens\":89},\"prompt_tokens_details\":{\"audio_tokens\":null,\"cached_tokens\":null,\"image_tokens\":5044,\"text_tokens\":586}}}"}, "scoring": {"f1_macro": 0.54, "f1_micro": 0.52, "cost_summary": {"total_input_tokens": 280558, "total_output_tokens": 5916, "total_tokens": 286474, "input_cost_usd": 0.0280558, "output_cost_usd": 0.0023664000000000003, "total_cost_usd": 0.030422199999999993}}, "normalized_score": 54.0}, {"_id": {"$oid": "69d4eb12b877594bc5718d6e"}, "test_id": "T0842", "benchmark": "business_letters", "date": "2026-03-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "alibaba", "model": "qwen3.5-27b", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false, \"base_url\": \"https://ws-wkjpbv6ov7sqlgqe.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\n \"metadata\": {\n \"send_date\": [\n \"1926-08-13\"\n ],\n \"letter_title\": [\n null\n ],\n \"sender_persons\": [\n \"Basler Rheinschiffahrt-Aktiengesellschaft\",\n \"Groschopf\",\n \"J.A. Ritter\"\n ],\n \"receiver_persons\": [\n \"Dr. Max Vischer\"\n ]\n }\n}", "model": "qwen3.5-27b", "provider": "alibaba", "finish_reason": "stop", "usage": {"input_tokens": 8152, "output_tokens": 112, "total_tokens": 8264, "input_cost_usd": 0.0024455999999999996, "output_cost_usd": 0.0002688, "estimated_cost_usd": 0.0027143999999999996}, "duration": 11.614383697509766, "timestamp": "2026-03-25T10:19:59.275555", "parsed": {"metadata": {"send_date": ["1926-08-13"], "letter_title": [null], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft", "Groschopf", "J.A. Ritter"], "receiver_persons": ["Dr. Max Vischer"], "document_number": "letter12"}}, "conversation_id": "49d20581-cf88-4d50-a4e2-8359e98d1bbf", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 2, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-0d26af9e-f586-907a-be80-ec2dfbc8476e\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1926-08-13\\\"\\n ],\\n \\\"letter_title\\\": [\\n null\\n ],\\n \\\"sender_persons\\\": [\\n \\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\",\\n \\\"Groschopf\\\",\\n \\\"J.A. Ritter\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Dr. Max Vischer\\\"\\n ]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"reasoning_content\":\"\"}}],\"created\":1774430399,\"model\":\"qwen3.5-27b\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":112,\"prompt_tokens\":8152,\"total_tokens\":8264,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":null,\"rejected_prediction_tokens\":null,\"text_tokens\":112},\"prompt_tokens_details\":{\"audio_tokens\":null,\"cached_tokens\":null,\"image_tokens\":7566,\"text_tokens\":586}}}"}, "scoring": {"f1_macro": 0.51, "f1_micro": 0.58, "cost_summary": {"total_input_tokens": 102920, "total_output_tokens": 2496, "total_tokens": 105416, "input_cost_usd": 0.030875999999999997, "output_cost_usd": 0.0059904, "total_cost_usd": 0.036866399999999994}}, "normalized_score": 51.0}, {"_id": {"$oid": "69d4eb12b877594bc5718d52"}, "test_id": "T0881", "benchmark": "business_letters", "date": "2026-03-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "alibaba", "model": "qwen3.5-flash-2026-02-23", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false, \"base_url\": \"https://ws-wkjpbv6ov7sqlgqe.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-02-27\"],\"letter_title\":null,\"sender_persons\":[\"Basler Personenschifffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.-G.\"]}}", "model": "qwen3.5-flash-2026-02-23", "provider": "alibaba", "finish_reason": "stop", "usage": {"input_tokens": 3108, "output_tokens": 95, "total_tokens": 3203, "input_cost_usd": 0.0003108, "output_cost_usd": 3.8e-05, "estimated_cost_usd": 0.0003488}, "duration": 6.026368856430054, "timestamp": "2026-03-25T10:35:25.422358", "parsed": {"metadata": {"send_date": ["1928-02-27"], "letter_title": null, "sender_persons": ["Basler Personenschifffahrtsgesellschaft"], "receiver_persons": ["Basler Rheinschiffahrt A.-G."], "document_number": "letter16"}}, "conversation_id": "e14ec226-afa0-41ba-b9d7-3cd5c8f68777", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-fe13a93e-48e9-9bea-8cb5-21c5b0fd5835\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1928-02-27\\\"\\n ],\\n \\\"letter_title\\\": null,\\n \\\"sender_persons\\\": [\\n \\\"Basler Personenschifffahrtsgesellschaft\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Basler Rheinschiffahrt A.-G.\\\"\\n ]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"reasoning_content\":\"\"}}],\"created\":1774431325,\"model\":\"qwen3.5-flash-2026-02-23\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":95,\"prompt_tokens\":3108,\"total_tokens\":3203,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":null,\"rejected_prediction_tokens\":null,\"text_tokens\":95},\"prompt_tokens_details\":{\"audio_tokens\":null,\"cached_tokens\":null,\"image_tokens\":2522,\"text_tokens\":586}}}"}, "scoring": {"f1_macro": 0.5, "f1_micro": 0.57, "cost_summary": {"total_input_tokens": 102920, "total_output_tokens": 2546, "total_tokens": 105466, "input_cost_usd": 0.010291999999999999, "output_cost_usd": 0.0010184, "total_cost_usd": 0.0113104}}, "normalized_score": 50.0}, {"_id": {"$oid": "69d4eb12b877594bc5718d4b"}, "test_id": "T0843", "benchmark": "business_letters", "date": "2026-03-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "alibaba", "model": "qwen3.5-27b", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true, \"base_url\": \"https://ws-wkjpbv6ov7sqlgqe.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-03-01\"],\"letter_title\":[\"Ihr Schreiben vom 27. Februar.\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Basler Personenschifffahrtsgesellschaft\"]}}", "model": "qwen3.5-27b", "provider": "alibaba", "finish_reason": "stop", "usage": {"input_tokens": 5630, "output_tokens": 111, "total_tokens": 5741, "input_cost_usd": 0.0016889999999999997, "output_cost_usd": 0.00026639999999999997, "estimated_cost_usd": 0.0019553999999999995}, "duration": 6.9586710929870605, "timestamp": "2026-03-25T10:20:08.751092", "parsed": {"metadata": {"send_date": ["1928-03-01"], "letter_title": ["Ihr Schreiben vom 27. Februar."], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Basler Personenschifffahrtsgesellschaft"], "document_number": "letter17"}}, "conversation_id": "e8950f94-1ab1-4535-bc4c-2b79b08a7832", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-3a5c4e0e-a544-97e0-b789-21bbec84db7a\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1928-03-01\\\"\\n ],\\n \\\"letter_title\\\": [\\n \\\"Ihr Schreiben vom 27. Februar.\\\"\\n ],\\n \\\"sender_persons\\\": [\\n \\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Basler Personenschifffahrtsgesellschaft\\\"\\n ]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"reasoning_content\":\"\"}}],\"created\":1774430409,\"model\":\"qwen3.5-27b\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":111,\"prompt_tokens\":5630,\"total_tokens\":5741,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":null,\"rejected_prediction_tokens\":null,\"text_tokens\":111},\"prompt_tokens_details\":{\"audio_tokens\":null,\"cached_tokens\":null,\"image_tokens\":5044,\"text_tokens\":586}}}"}, "scoring": {"f1_macro": 0.59, "f1_micro": 0.53, "cost_summary": {"total_input_tokens": 177638, "total_output_tokens": 3114, "total_tokens": 180752, "input_cost_usd": 0.05329140000000001, "output_cost_usd": 0.007473599999999999, "total_cost_usd": 0.06076499999999999}}, "normalized_score": 59.0}, {"_id": {"$oid": "69d4eb12b877594bc5718d6a"}, "test_id": "T0841", "benchmark": "business_letters", "date": "2026-03-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "alibaba", "model": "qwen3.5-27b", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"base_url\": \"https://ws-wkjpbv6ov7sqlgqe.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-03-01\"],\"letter_title\":[\"Ihr Schreiben vom 27. Februar.\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Basler Personenschifffahrtsgesellschaft\"]}}", "model": "qwen3.5-27b", "provider": "alibaba", "finish_reason": "stop", "usage": {"input_tokens": 5630, "output_tokens": 111, "total_tokens": 5741, "input_cost_usd": 0.0016889999999999997, "output_cost_usd": 0.00026639999999999997, "estimated_cost_usd": 0.0019553999999999995}, "duration": 16.935202836990356, "timestamp": "2026-03-25T10:19:13.548623", "parsed": {"metadata": {"send_date": ["1928-03-01"], "letter_title": ["Ihr Schreiben vom 27. Februar."], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Basler Personenschifffahrtsgesellschaft"], "document_number": "letter17"}}, "conversation_id": "ada335e8-62db-46e4-93f3-4b86620bbbd6", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-3e0912f4-5a2a-98a5-bfe6-e31d4bcd1608\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1928-03-01\\\"\\n ],\\n \\\"letter_title\\\": [\\n \\\"Ihr Schreiben vom 27. Februar.\\\"\\n ],\\n \\\"sender_persons\\\": [\\n \\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Basler Personenschifffahrtsgesellschaft\\\"\\n ]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"reasoning_content\":\"\"}}],\"created\":1774430353,\"model\":\"qwen3.5-27b\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":111,\"prompt_tokens\":5630,\"total_tokens\":5741,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":null,\"rejected_prediction_tokens\":null,\"text_tokens\":111},\"prompt_tokens_details\":{\"audio_tokens\":null,\"cached_tokens\":null,\"image_tokens\":5044,\"text_tokens\":586}}}"}, "scoring": {"f1_macro": 0.55, "f1_micro": 0.55, "cost_summary": {"total_input_tokens": 280558, "total_output_tokens": 5620, "total_tokens": 286178, "input_cost_usd": 0.08416740000000002, "output_cost_usd": 0.013488000000000002, "total_cost_usd": 0.0976554}}, "normalized_score": 55.00000000000001}, {"_id": {"$oid": "69d4eb12b877594bc5718d56"}, "test_id": "T0856", "benchmark": "business_letters", "date": "2026-03-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "alibaba", "model": "qwen3.5-122b-a10b", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true, \"base_url\": \"https://ws-wkjpbv6ov7sqlgqe.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\n \"metadata\": {\n \"send_date\": [\"1932-10-04\"],\n \"letter_title\": [null],\n \"sender_persons\": [\"Basler Rheinschiffahrt Aktiengesellschaft\"],\n \"receiver_persons\": [\"Dr. Max Vischer\"]\n }\n}", "model": "qwen3.5-122b-a10b", "provider": "alibaba", "finish_reason": "stop", "usage": {"input_tokens": 8152, "output_tokens": 74, "total_tokens": 8226, "input_cost_usd": 0.0032608, "output_cost_usd": 0.0002368, "estimated_cost_usd": 0.0034976}, "duration": 12.879505634307861, "timestamp": "2026-03-25T10:19:29.837267", "parsed": {"metadata": {"send_date": ["1932-10-04"], "letter_title": [null], "sender_persons": ["Basler Rheinschiffahrt Aktiengesellschaft"], "receiver_persons": ["Dr. Max Vischer"], "document_number": "letter52"}}, "conversation_id": "279835d6-d5eb-497d-a710-c58088d8e361", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-39f432cd-9b69-938c-affe-78c8079a986a\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1932-10-04\\\"],\\n \\\"letter_title\\\": [null],\\n \\\"sender_persons\\\": [\\\"Basler Rheinschiffahrt Aktiengesellschaft\\\"],\\n \\\"receiver_persons\\\": [\\\"Dr. Max Vischer\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"reasoning_content\":\"\"}}],\"created\":1774430370,\"model\":\"qwen3.5-122b-a10b\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":74,\"prompt_tokens\":8152,\"total_tokens\":8226,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":null,\"rejected_prediction_tokens\":null,\"text_tokens\":74},\"prompt_tokens_details\":{\"audio_tokens\":null,\"cached_tokens\":null,\"image_tokens\":7566,\"text_tokens\":586}}}"}, "scoring": {"f1_macro": 0.57, "f1_micro": 0.53, "cost_summary": {"total_input_tokens": 177638, "total_output_tokens": 2478, "total_tokens": 180116, "input_cost_usd": 0.0710552, "output_cost_usd": 0.0079296, "total_cost_usd": 0.0789848}}, "normalized_score": 56.99999999999999}, {"_id": {"$oid": "69d4eb12b877594bc5718d3b"}, "test_id": "T0828", "benchmark": "business_letters", "date": "2026-03-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "alibaba", "model": "qwen3.5-35b-a3b", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"base_url\": \"https://ws-wkjpbv6ov7sqlgqe.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-03-22\"],\"letter_title\":[\"Letter regarding the purchase of the ship 'Rheinfelden' and rental negotiations\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\",\"Sulich\",\"Gundlach\"],\"receiver_persons\":[\"Vorstand der Basler Personenschiffahrtsgesellschaft\"]}}", "model": "qwen3.5-35b-a3b", "provider": "alibaba", "finish_reason": "stop", "usage": {"input_tokens": 10674, "output_tokens": 134, "total_tokens": 10808, "input_cost_usd": 0.0026685, "output_cost_usd": 0.000268, "estimated_cost_usd": 0.0029365}, "duration": 12.158033847808838, "timestamp": "2026-03-25T10:14:09.751369", "parsed": {"metadata": {"letter_title": ["Letter regarding the purchase of the ship 'Rheinfelden' and rental negotiations"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft", "Sulich", "Gundlach"], "send_date": ["1928-03-22"], "receiver_persons": ["Vorstand der Basler Personenschiffahrtsgesellschaft"], "document_number": "letter19"}}, "conversation_id": "5938e373-ddb5-4e03-a9b5-0cc58efbbe5e", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 3, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-1ed19ddb-077e-9bea-8398-714c2ece9179\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [\\n \\\"Letter regarding the purchase of the ship 'Rheinfelden' and rental negotiations\\\"\\n ],\\n \\\"sender_persons\\\": [\\n \\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\",\\n \\\"Sulich\\\",\\n \\\"Gundlach\\\"\\n ],\\n \\\"send_date\\\": [\\n \\\"1928-03-22\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Vorstand der Basler Personenschiffahrtsgesellschaft\\\"\\n ]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"reasoning_content\":\"\"}}],\"created\":1774430050,\"model\":\"qwen3.5-35b-a3b\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":134,\"prompt_tokens\":10674,\"total_tokens\":10808,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":null,\"rejected_prediction_tokens\":null,\"text_tokens\":134},\"prompt_tokens_details\":{\"audio_tokens\":null,\"cached_tokens\":null,\"image_tokens\":10088,\"text_tokens\":586}}}"}, "scoring": {"f1_macro": 0.55, "f1_micro": 0.54, "cost_summary": {"total_input_tokens": 280558, "total_output_tokens": 5610, "total_tokens": 286168, "input_cost_usd": 0.07013949999999998, "output_cost_usd": 0.011219999999999999, "total_cost_usd": 0.0813595}}, "normalized_score": 55.00000000000001}, {"_id": {"$oid": "69d4eb12b877594bc5718d6b"}, "test_id": "T0829", "benchmark": "business_letters", "date": "2026-03-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "alibaba", "model": "qwen3.5-35b-a3b", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false, \"base_url\": \"https://ws-wkjpbv6ov7sqlgqe.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-03-24\"],\"letter_title\":[\"Verkauf\"],\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.-G.\"]}}", "model": "qwen3.5-35b-a3b", "provider": "alibaba", "finish_reason": "stop", "usage": {"input_tokens": 5630, "output_tokens": 103, "total_tokens": 5733, "input_cost_usd": 0.0014075, "output_cost_usd": 0.000206, "estimated_cost_usd": 0.0016135}, "duration": 6.821973085403442, "timestamp": "2026-03-25T10:14:26.925409", "parsed": {"metadata": {"send_date": ["1928-03-24"], "letter_title": ["Verkauf"], "sender_persons": ["Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["Basler Rheinschiffahrt A.-G."], "document_number": "letter20"}}, "conversation_id": "248ec30d-ff9a-4a05-921b-e57eff7db8b7", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-ca71d2eb-be0e-9950-bac4-10555b7898e5\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1928-03-24\\\"\\n ],\\n \\\"letter_title\\\": [\\n \\\"Verkauf\\\"\\n ],\\n \\\"sender_persons\\\": [\\n \\\"Basler Personenschiffahrtsgesellschaft\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Basler Rheinschiffahrt A.-G.\\\"\\n ]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"reasoning_content\":\"\"}}],\"created\":1774430067,\"model\":\"qwen3.5-35b-a3b\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":103,\"prompt_tokens\":5630,\"total_tokens\":5733,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":null,\"rejected_prediction_tokens\":null,\"text_tokens\":103},\"prompt_tokens_details\":{\"audio_tokens\":null,\"cached_tokens\":null,\"image_tokens\":5044,\"text_tokens\":586}}}"}, "scoring": {"f1_macro": 0.5, "f1_micro": 0.57, "cost_summary": {"total_input_tokens": 102920, "total_output_tokens": 2418, "total_tokens": 105338, "input_cost_usd": 0.025729999999999992, "output_cost_usd": 0.004836, "total_cost_usd": 0.030566000000000006}}, "normalized_score": 50.0}, {"_id": {"$oid": "69d4eb12b877594bc5718d73"}, "test_id": "T0868", "benchmark": "business_letters", "date": "2026-03-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "alibaba", "model": "qwen3.5-397b-a17b", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false, \"base_url\": \"https://ws-wkjpbv6ov7sqlgqe.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\n \"metadata\": {\n \"send_date\": [\n \"1928-02-27\"\n ],\n \"letter_title\": [\n null\n ],\n \"sender_persons\": [\n \"Basler Personenschiffahrtsgesellschaft\"\n ],\n \"receiver_persons\": [\n \"Basler Rheinschiffahrt A.-G.\"\n ]\n }\n}", "model": "qwen3.5-397b-a17b", "provider": "alibaba", "finish_reason": "stop", "usage": {"input_tokens": 3108, "output_tokens": 99, "total_tokens": 3207, "input_cost_usd": 0.0018648, "output_cost_usd": 0.0003564, "estimated_cost_usd": 0.0022212}, "duration": 7.614291667938232, "timestamp": "2026-03-25T10:19:14.988523", "parsed": {"metadata": {"send_date": ["1928-02-27"], "letter_title": [null], "sender_persons": ["Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["Basler Rheinschiffahrt A.-G."], "document_number": "letter16"}}, "conversation_id": "210bdbb9-95da-4cf5-8628-687c701cb6a8", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-4b7b324e-0261-9173-8571-45d16e056cb4\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1928-02-27\\\"\\n ],\\n \\\"letter_title\\\": [\\n null\\n ],\\n \\\"sender_persons\\\": [\\n \\\"Basler Personenschiffahrtsgesellschaft\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Basler Rheinschiffahrt A.-G.\\\"\\n ]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"reasoning_content\":\"\"}}],\"created\":1774430355,\"model\":\"qwen3.5-397b-a17b\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":99,\"prompt_tokens\":3108,\"total_tokens\":3207,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":null,\"rejected_prediction_tokens\":null,\"text_tokens\":99},\"prompt_tokens_details\":{\"audio_tokens\":null,\"cached_tokens\":null,\"image_tokens\":2522,\"text_tokens\":586}}}"}, "scoring": {"f1_macro": 0.52, "f1_micro": 0.61, "cost_summary": {"total_input_tokens": 102920, "total_output_tokens": 2300, "total_tokens": 105220, "input_cost_usd": 0.061751999999999994, "output_cost_usd": 0.00828, "total_cost_usd": 0.070032}}, "normalized_score": 52.0}, {"_id": {"$oid": "69d4eb12b877594bc5718d60"}, "test_id": "T0854", "benchmark": "business_letters", "date": "2026-03-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "alibaba", "model": "qwen3.5-122b-a10b", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"base_url\": \"https://ws-wkjpbv6ov7sqlgqe.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-04-04\"],\"letter_title\":[\"Betrifft Kauf 'Rheinfelden'\"],\"sender_persons\":[\"G. Schmid\",\"Julius\"],\"receiver_persons\":[\"Basler Personenschiffahrtsgesellschaft\"]}}", "model": "qwen3.5-122b-a10b", "provider": "alibaba", "finish_reason": "stop", "usage": {"input_tokens": 5630, "output_tokens": 84, "total_tokens": 5714, "input_cost_usd": 0.002252, "output_cost_usd": 0.0002688, "estimated_cost_usd": 0.0025208}, "duration": 7.987709999084473, "timestamp": "2026-03-25T10:18:39.563483", "parsed": {"metadata": {"send_date": ["1928-04-04"], "letter_title": ["Betrifft Kauf 'Rheinfelden'"], "sender_persons": ["G. Schmid", "Julius"], "receiver_persons": ["Basler Personenschiffahrtsgesellschaft"], "document_number": "letter25"}}, "conversation_id": "8b78e58d-9386-43d7-addf-761de552a730", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 2, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-40905c1f-8dd1-9ca2-9960-25dafe40726b\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1928-04-04\\\"],\\n \\\"letter_title\\\": [\\\"Betrifft Kauf 'Rheinfelden'\\\"],\\n \\\"sender_persons\\\": [\\\"G. Schmid\\\", \\\"Julius\\\"],\\n \\\"receiver_persons\\\": [\\\"Basler Personenschiffahrtsgesellschaft\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"reasoning_content\":\"\"}}],\"created\":1774430320,\"model\":\"qwen3.5-122b-a10b\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":84,\"prompt_tokens\":5630,\"total_tokens\":5714,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":null,\"rejected_prediction_tokens\":null,\"text_tokens\":84},\"prompt_tokens_details\":{\"audio_tokens\":null,\"cached_tokens\":null,\"image_tokens\":5044,\"text_tokens\":586}}}"}, "scoring": {"f1_macro": 0.55, "f1_micro": 0.55, "cost_summary": {"total_input_tokens": 280558, "total_output_tokens": 4399, "total_tokens": 284957, "input_cost_usd": 0.1122232, "output_cost_usd": 0.014076799999999999, "total_cost_usd": 0.1263}}, "normalized_score": 55.00000000000001}, {"_id": {"$oid": "69d4eb12b877594bc5718d65"}, "test_id": "T0855", "benchmark": "business_letters", "date": "2026-03-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "alibaba", "model": "qwen3.5-122b-a10b", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false, \"base_url\": \"https://ws-wkjpbv6ov7sqlgqe.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\n \"metadata\": {\n \"send_date\": [\"1928-05-15\"],\n \"letter_title\": [null],\n \"sender_persons\": [null],\n \"receiver_persons\": [\"Basler Rheinschiffahrt-Aktiengesellschaft\"]\n }\n}", "model": "qwen3.5-122b-a10b", "provider": "alibaba", "finish_reason": "stop", "usage": {"input_tokens": 3108, "output_tokens": 70, "total_tokens": 3178, "input_cost_usd": 0.0012432, "output_cost_usd": 0.000224, "estimated_cost_usd": 0.0014672}, "duration": 10.526345252990723, "timestamp": "2026-03-25T10:19:04.185312", "parsed": {"metadata": {"send_date": ["1928-05-15"], "letter_title": [null], "sender_persons": [null], "receiver_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "document_number": "letter36"}}, "conversation_id": "1c5e8581-3478-4586-91d9-36ea016878b1", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-56d795ef-1c1d-9bc3-980f-ed5ffa11890d\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1928-05-15\\\"],\\n \\\"letter_title\\\": [null],\\n \\\"sender_persons\\\": [null],\\n \\\"receiver_persons\\\": [\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"reasoning_content\":\"\"}}],\"created\":1774430344,\"model\":\"qwen3.5-122b-a10b\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":70,\"prompt_tokens\":3108,\"total_tokens\":3178,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":null,\"rejected_prediction_tokens\":null,\"text_tokens\":70},\"prompt_tokens_details\":{\"audio_tokens\":null,\"cached_tokens\":null,\"image_tokens\":2522,\"text_tokens\":586}}}"}, "scoring": {"f1_macro": 0.53, "f1_micro": 0.61, "cost_summary": {"total_input_tokens": 102920, "total_output_tokens": 1902, "total_tokens": 104822, "input_cost_usd": 0.041167999999999996, "output_cost_usd": 0.0060864000000000005, "total_cost_usd": 0.0472544}}, "normalized_score": 53.0}, {"_id": {"$oid": "69d4eb12b877594bc5718d37"}, "test_id": "T0882", "benchmark": "business_letters", "date": "2026-03-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "alibaba", "model": "qwen3.5-flash-2026-02-23", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true, \"base_url\": \"https://ws-wkjpbv6ov7sqlgqe.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-12-19\"],\"letter_title\":[\"Betr. Personenschiffahrt\"],\"sender_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft\"],\"receiver_persons\":[\"Dr.M.Vischer - von Planta\"]}}", "model": "qwen3.5-flash-2026-02-23", "provider": "alibaba", "finish_reason": "stop", "usage": {"input_tokens": 3108, "output_tokens": 107, "total_tokens": 3215, "input_cost_usd": 0.0003108, "output_cost_usd": 4.2800000000000004e-05, "estimated_cost_usd": 0.00035360000000000003}, "duration": 6.735973834991455, "timestamp": "2026-03-25T10:35:34.556460", "parsed": {"metadata": {"send_date": ["1932-12-19"], "letter_title": ["Betr. Personenschiffahrt"], "sender_persons": ["Basler Rheinschiffahrt Aktiengesellschaft"], "receiver_persons": ["Dr.M.Vischer - von Planta"], "document_number": "letter60"}}, "conversation_id": "99ced110-491a-4257-878d-4ce1188ba72f", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"chatcmpl-d1de961e-0f3c-925d-acec-d158e0024a64\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1932-12-19\\\"\\n ],\\n \\\"letter_title\\\": [\\n \\\"Betr. Personenschiffahrt\\\"\\n ],\\n \\\"sender_persons\\\": [\\n \\\"Basler Rheinschiffahrt Aktiengesellschaft\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Dr.M.Vischer - von Planta\\\"\\n ]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"reasoning_content\":\"\"}}],\"created\":1774431335,\"model\":\"qwen3.5-flash-2026-02-23\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":107,\"prompt_tokens\":3108,\"total_tokens\":3215,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":null,\"rejected_prediction_tokens\":null,\"text_tokens\":107},\"prompt_tokens_details\":{\"audio_tokens\":null,\"cached_tokens\":null,\"image_tokens\":2522,\"text_tokens\":586}}}"}, "scoring": {"f1_macro": 0.57, "f1_micro": 0.51, "cost_summary": {"total_input_tokens": 177638, "total_output_tokens": 3323, "total_tokens": 180961, "input_cost_usd": 0.0177638, "output_cost_usd": 0.0013292, "total_cost_usd": 0.019092999999999995}}, "normalized_score": 56.99999999999999}, {"_id": {"$oid": "69d4eb12b877594bc5718d55"}, "test_id": "T0830", "benchmark": "business_letters", "date": "2026-03-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "alibaba", "model": "qwen3.5-35b-a3b", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true, \"base_url\": \"https://ws-wkjpbv6ov7sqlgqe.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-06-19\"],\"letter_title\":null,\"sender_persons\":[\"Dr. Adolf Bieder\",\"Dr. Hans Burckhardt\",\"Dr. Rudolf Leupold\"],\"receiver_persons\":[\"Basler Personenschiffahrtsgesellschaft\"]}}", "model": "qwen3.5-35b-a3b", "provider": "alibaba", "finish_reason": "stop", "usage": {"input_tokens": 3108, "output_tokens": 109, "total_tokens": 3217, "input_cost_usd": 0.000777, "output_cost_usd": 0.000218, "estimated_cost_usd": 0.000995}, "duration": 5.080926179885864, "timestamp": "2026-03-25T10:14:40.160219", "parsed": {"metadata": {"send_date": ["1928-06-19"], "letter_title": null, "sender_persons": ["Dr. Adolf Bieder", "Dr. Hans Burckhardt", "Dr. Rudolf Leupold"], "receiver_persons": ["Basler Personenschiffahrtsgesellschaft"], "document_number": "letter43"}}, "conversation_id": "d75120f3-e554-494c-8dd6-28b01fabfedb", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 1, "sender_persons_fp": 2, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-105d5cfa-09b2-9e4b-8409-eb6032993d0d\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1928-06-19\\\"\\n ],\\n \\\"letter_title\\\": null,\\n \\\"sender_persons\\\": [\\n \\\"Dr. Adolf Bieder\\\",\\n \\\"Dr. Hans Burckhardt\\\",\\n \\\"Dr. Rudolf Leupold\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Basler Personenschiffahrtsgesellschaft\\\"\\n ]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"reasoning_content\":\"\"}}],\"created\":1774430080,\"model\":\"qwen3.5-35b-a3b\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":109,\"prompt_tokens\":3108,\"total_tokens\":3217,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":null,\"rejected_prediction_tokens\":null,\"text_tokens\":109},\"prompt_tokens_details\":{\"audio_tokens\":null,\"cached_tokens\":null,\"image_tokens\":2522,\"text_tokens\":586}}}"}, "scoring": {"f1_macro": 0.58, "f1_micro": 0.52, "cost_summary": {"total_input_tokens": 177638, "total_output_tokens": 3247, "total_tokens": 180885, "input_cost_usd": 0.04440949999999999, "output_cost_usd": 0.006494000000000001, "total_cost_usd": 0.0509035}}, "normalized_score": 57.99999999999999}, {"_id": {"$oid": "69d4eb12b877594bc5718d4d"}, "test_id": "T0869", "benchmark": "business_letters", "date": "2026-03-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "alibaba", "model": "qwen3.5-397b-a17b", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true, \"base_url\": \"https://ws-wkjpbv6ov7sqlgqe.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-09-07\"],\"letter_title\":[\"Betr. Personenschiffahrt\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Dr. M. Vischer-von Planta\"]}}", "model": "qwen3.5-397b-a17b", "provider": "alibaba", "finish_reason": "stop", "usage": {"input_tokens": 8152, "output_tokens": 108, "total_tokens": 8260, "input_cost_usd": 0.004891199999999999, "output_cost_usd": 0.0003888, "estimated_cost_usd": 0.005279999999999999}, "duration": 8.12558913230896, "timestamp": "2026-03-25T10:19:43.316199", "parsed": {"metadata": {"send_date": ["1932-09-07"], "letter_title": ["Betr. Personenschiffahrt"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Dr. M. Vischer-von Planta"], "document_number": "letter48"}}, "conversation_id": "baf39605-ae98-45db-8dd3-eea8ebba4001", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-5c6ffa38-e3aa-9713-b4ad-eb49b0cab1d7\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1932-09-07\\\"\\n ],\\n \\\"letter_title\\\": [\\n \\\"Betr. Personenschiffahrt\\\"\\n ],\\n \\\"sender_persons\\\": [\\n \\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Dr. M. Vischer-von Planta\\\"\\n ]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"reasoning_content\":\"\"}}],\"created\":1774430383,\"model\":\"qwen3.5-397b-a17b\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":108,\"prompt_tokens\":8152,\"total_tokens\":8260,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":null,\"rejected_prediction_tokens\":null,\"text_tokens\":108},\"prompt_tokens_details\":{\"audio_tokens\":null,\"cached_tokens\":null,\"image_tokens\":7566,\"text_tokens\":586}}}"}, "scoring": {"f1_macro": 0.61, "f1_micro": 0.56, "cost_summary": {"total_input_tokens": 177638, "total_output_tokens": 3086, "total_tokens": 180724, "input_cost_usd": 0.10658280000000002, "output_cost_usd": 0.011109599999999999, "total_cost_usd": 0.11769239999999999}}, "normalized_score": 61.0}, {"_id": {"$oid": "69d4eb12b877594bc5718d31"}, "test_id": "T0816", "benchmark": "business_letters", "date": "2026-03-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "alibaba", "model": "qwen3.5-plus-2026-02-15", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false, \"base_url\": \"https://ws-wkjpbv6ov7sqlgqe.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\n \"metadata\": {\n \"send_date\": [\n \"1928-05-03\"\n ],\n \"letter_title\": [\n null\n ],\n \"sender_persons\": [\n \"Ritter\",\n \"Groschupf\"\n ],\n \"receiver_persons\": [\n \"W. Stauffacher\"\n ]\n }\n}", "model": "qwen3.5-plus", "provider": "alibaba", "finish_reason": "stop", "usage": {"input_tokens": 3108, "output_tokens": 96, "total_tokens": 3204, "input_cost_usd": 0.0012432, "output_cost_usd": 0.0002304, "estimated_cost_usd": 0.0014736}, "duration": 8.665979385375977, "timestamp": "2026-03-24T18:40:34.025855", "parsed": {"metadata": {"send_date": ["1928-05-03"], "letter_title": [null], "sender_persons": ["Ritter", "Groschupf"], "receiver_persons": ["W. Stauffacher"], "document_number": "letter32"}}, "conversation_id": "e5f6c0b3-13b1-49f0-9201-fff6d8579224", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 2, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-537b9e0b-fa77-9f89-a354-c52509b59824\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1928-05-03\\\"\\n ],\\n \\\"letter_title\\\": [\\n null\\n ],\\n \\\"sender_persons\\\": [\\n \\\"Ritter\\\",\\n \\\"Groschupf\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"W. Stauffacher\\\"\\n ]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"reasoning_content\":\"\"}}],\"created\":1774374034,\"model\":\"qwen3.5-plus\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":96,\"prompt_tokens\":3108,\"total_tokens\":3204,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":null,\"rejected_prediction_tokens\":null,\"text_tokens\":96},\"prompt_tokens_details\":{\"audio_tokens\":null,\"cached_tokens\":null,\"image_tokens\":2522,\"text_tokens\":586}}}"}, "scoring": {"f1_macro": 0.56, "f1_micro": 0.64, "cost_summary": {"total_input_tokens": 102920, "total_output_tokens": 2305, "total_tokens": 105225, "input_cost_usd": 0.041167999999999996, "output_cost_usd": 0.0055320000000000005, "total_cost_usd": 0.046700000000000005}}, "normalized_score": 56.00000000000001}, {"_id": {"$oid": "69d4eb12b877594bc5718d26"}, "test_id": "T0817", "benchmark": "business_letters", "date": "2026-03-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "alibaba", "model": "qwen3.5-plus-2026-02-15", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true, \"base_url\": \"https://ws-wkjpbv6ov7sqlgqe.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\n \"metadata\": {\n \"send_date\": [\n \"1932-10-07\"\n ],\n \"letter_title\": [\n null\n ],\n \"sender_persons\": [\n \"Basler Personenschiffahrtsgesellschaft\"\n ],\n \"receiver_persons\": [\n \"Vorstandsmitglieder der Basler Personenschiffahrtsgesellschaft\"\n ]\n }\n}", "model": "qwen3.5-plus", "provider": "alibaba", "finish_reason": "stop", "usage": {"input_tokens": 3108, "output_tokens": 102, "total_tokens": 3210, "input_cost_usd": 0.0012432, "output_cost_usd": 0.0002448, "estimated_cost_usd": 0.0014880000000000002}, "duration": 7.078776597976685, "timestamp": "2026-03-24T18:42:47.862061", "parsed": {"metadata": {"send_date": ["1932-10-07"], "letter_title": [null], "sender_persons": ["Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["Vorstandsmitglieder der Basler Personenschiffahrtsgesellschaft"], "document_number": "letter53"}}, "conversation_id": "5400e92b-8be2-45fc-9a7e-b39ff7c73188", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-fa084292-d105-92d7-95bb-a0949dc7ac9f\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1932-10-07\\\"\\n ],\\n \\\"letter_title\\\": [\\n null\\n ],\\n \\\"sender_persons\\\": [\\n \\\"Basler Personenschiffahrtsgesellschaft\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Vorstandsmitglieder der Basler Personenschiffahrtsgesellschaft\\\"\\n ]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"reasoning_content\":\"\"}}],\"created\":1774374168,\"model\":\"qwen3.5-plus\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":102,\"prompt_tokens\":3108,\"total_tokens\":3210,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":null,\"rejected_prediction_tokens\":null,\"text_tokens\":102},\"prompt_tokens_details\":{\"audio_tokens\":null,\"cached_tokens\":null,\"image_tokens\":2522,\"text_tokens\":586}}}"}, "scoring": {"f1_macro": 0.61, "f1_micro": 0.56, "cost_summary": {"total_input_tokens": 177638, "total_output_tokens": 3097, "total_tokens": 180735, "input_cost_usd": 0.0710552, "output_cost_usd": 0.007432800000000001, "total_cost_usd": 0.078488}}, "normalized_score": 61.0}, {"_id": {"$oid": "69d4eb12b877594bc5718d2a"}, "test_id": "T0815", "benchmark": "business_letters", "date": "2026-03-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "alibaba", "model": "qwen3.5-plus-2026-02-15", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"base_url\": \"https://ws-wkjpbv6ov7sqlgqe.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\n \"metadata\": {\n \"send_date\": [\"1928-05-03\"],\n \"letter_title\": [null],\n \"sender_persons\": [\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\n \"receiver_persons\": [\"Dr. Max Vischer\"]\n }\n}", "model": "qwen3.5-plus", "provider": "alibaba", "finish_reason": "stop", "usage": {"input_tokens": 3108, "output_tokens": 74, "total_tokens": 3182, "input_cost_usd": 0.0012432, "output_cost_usd": 0.00017759999999999998, "estimated_cost_usd": 0.0014208}, "duration": 17.36755895614624, "timestamp": "2026-03-24T18:33:21.233158", "parsed": {"metadata": {"send_date": ["1928-05-03"], "letter_title": [null], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Dr. Max Vischer"], "document_number": "letter31"}}, "conversation_id": "ad3c427b-b133-49e7-8ed3-781fef42e5c5", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-fb56a260-b10b-96d0-8b63-b58199a6735a\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1928-05-03\\\"],\\n \\\"letter_title\\\": [null],\\n \\\"sender_persons\\\": [\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"],\\n \\\"receiver_persons\\\": [\\\"Dr. Max Vischer\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"reasoning_content\":\"\"}}],\"created\":1774373601,\"model\":\"qwen3.5-plus\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":74,\"prompt_tokens\":3108,\"total_tokens\":3182,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":null,\"rejected_prediction_tokens\":null,\"text_tokens\":74},\"prompt_tokens_details\":{\"audio_tokens\":null,\"cached_tokens\":null,\"image_tokens\":2522,\"text_tokens\":586}}}"}, "scoring": {"f1_macro": 0.59, "f1_micro": 0.59, "cost_summary": {"total_input_tokens": 280558, "total_output_tokens": 5320, "total_tokens": 285878, "input_cost_usd": 0.1122232, "output_cost_usd": 0.012768, "total_cost_usd": 0.12499119999999998}}, "normalized_score": 59.0}, {"_id": {"$oid": "69d4eb12b877594bc5718d1d"}, "test_id": "T0720", "benchmark": "business_letters", "date": "2026-03-23", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "x-ai", "model": "grok-4.20-0309-reasoning", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1912-12-16\"],\"letter_title\":null,\"sender_persons\":[\"Basler Processions- und Wallfahrts-Verein\"],\"receiver_persons\":[\"Basler Rheinschifffahrt A.-G.\"]}}", "model": "grok-4.20-0309-reasoning", "provider": "x-ai", "finish_reason": "stop", "usage": {"input_tokens": 815, "output_tokens": 69, "total_tokens": 2928, "cached_tokens": 768, "input_cost_usd": 0.00163, "output_cost_usd": 0.000414, "estimated_cost_usd": 0.002044}, "duration": 22.575246572494507, "timestamp": "2026-03-23T13:56:28.236887", "parsed": {"metadata": {"send_date": ["1912-12-16"], "letter_title": null, "sender_persons": ["Basler Processions- und Wallfahrts-Verein"], "receiver_persons": ["Basler Rheinschifffahrt A.-G."], "document_number": "letter59"}}, "conversation_id": "6247ca0e-a9f9-47ee-8764-d4b3cbb5c2c2", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"1ab1a51c-47ae-9ad2-9f62-3f2160b0ad7d\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1912-12-16\\\"],\\n \\\"letter_title\\\": null,\\n \\\"sender_persons\\\": [\\\"Basler Processions- und Wallfahrts-Verein\\\"],\\n \\\"receiver_persons\\\": [\\\"Basler Rheinschifffahrt A.-G.\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1912-12-16\"],\"letter_title\":null,\"sender_persons\":[\"Basler Processions- und Wallfahrts-Verein\"],\"receiver_persons\":[\"Basler Rheinschifffahrt A.-G.\"]}}}}],\"created\":1774270587,\"model\":\"grok-4.20-0309-reasoning\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":\"fp_d6e36c82c2\",\"usage\":{\"completion_tokens\":69,\"prompt_tokens\":815,\"total_tokens\":2928,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":2044,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":768,\"text_tokens\":623,\"image_tokens\":192},\"num_sources_used\":0,\"cost_in_usd_ticks\":132156000}}"}, "scoring": {"f1_macro": 0.15, "f1_micro": 0.18, "cost_summary": {"total_input_tokens": 22315, "total_output_tokens": 1364, "total_tokens": 23679, "input_cost_usd": 0.04462999999999999, "output_cost_usd": 0.008184000000000002, "total_cost_usd": 0.05281399999999998}}, "normalized_score": 15.0}, {"_id": {"$oid": "69d4eb12b877594bc5718ced"}, "test_id": "T0694", "benchmark": "business_letters", "date": "2026-03-23", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5.3-codex", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"api_style\":\"responses\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\n \"metadata\": {\n \"send_date\": [\"1935-08-16\"],\n \"letter_title\": null,\n \"sender_persons\": null,\n \"receiver_persons\": [\"Basler Personenschiffahrts-Gesellschaft\"]\n }\n}", "model": "gpt-5.3-codex", "provider": "openai", "finish_reason": "completed", "usage": {"input_tokens": 2327, "output_tokens": 59, "total_tokens": 2386, "input_cost_usd": 0.00407225, "output_cost_usd": 0.0008259999999999999, "estimated_cost_usd": 0.00489825}, "duration": 2.198643207550049, "timestamp": "2026-03-23T21:39:49.913699", "parsed": {"metadata": {"send_date": ["1935-08-16"], "letter_title": null, "sender_persons": null, "receiver_persons": ["Basler Personenschiffahrts-Gesellschaft"], "document_number": "letter64"}}, "conversation_id": "564de69e-9633-4dbf-b149-a7a5b128cc89", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"resp_01272a237d85d7bf0069c1a514cb788196b3874c08499201bc\",\"created_at\":1774298388.0,\"error\":null,\"incomplete_details\":null,\"instructions\":\"You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history\",\"metadata\":{},\"model\":\"gpt-5.3-codex\",\"object\":\"response\",\"output\":[{\"id\":\"msg_01272a237d85d7bf0069c1a5156a1081968f2309d7a7e36b41\",\"content\":[{\"annotations\":[],\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1935-08-16\\\"],\\n \\\"letter_title\\\": null,\\n \\\"sender_persons\\\": null,\\n \\\"receiver_persons\\\": [\\\"Basler Personenschiffahrts-Gesellschaft\\\"]\\n }\\n}\",\"type\":\"output_text\",\"logprobs\":[]}],\"role\":\"assistant\",\"status\":\"completed\",\"type\":\"message\",\"phase\":\"final_answer\"}],\"parallel_tool_calls\":true,\"temperature\":0.0,\"tool_choice\":\"auto\",\"tools\":[],\"top_p\":0.98,\"background\":false,\"completed_at\":1774298390.0,\"conversation\":null,\"max_output_tokens\":null,\"max_tool_calls\":null,\"previous_response_id\":null,\"prompt\":null,\"prompt_cache_key\":null,\"prompt_cache_retention\":null,\"reasoning\":{\"effort\":\"none\",\"generate_summary\":null,\"summary\":null},\"safety_identifier\":null,\"service_tier\":\"default\",\"status\":\"completed\",\"text\":{\"format\":{\"type\":\"text\"},\"verbosity\":\"medium\"},\"top_logprobs\":0,\"truncation\":\"disabled\",\"usage\":{\"input_tokens\":2327,\"input_tokens_details\":{\"cached_tokens\":0},\"output_tokens\":59,\"output_tokens_details\":{\"reasoning_tokens\":0},\"total_tokens\":2386},\"user\":null,\"billing\":{\"payer\":\"developer\"},\"frequency_penalty\":0.0,\"presence_penalty\":0.0,\"store\":true}"}, "scoring": {"f1_macro": 0.57, "f1_micro": 0.59, "cost_summary": {"total_input_tokens": 205086, "total_output_tokens": 3340, "total_tokens": 208426, "input_cost_usd": 0.35890049999999996, "output_cost_usd": 0.04676, "total_cost_usd": 0.4056605000000001}}, "normalized_score": 56.99999999999999}, {"_id": {"$oid": "69d4eb12b877594bc5718ce5"}, "test_id": "T0114", "benchmark": "business_letters", "date": "2026-03-23", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5-nano", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-06-22\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"Basler Schiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Herrn P. Christ - Wackernagel\"]}}", "model": "gpt-5-nano-2025-08-07", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 2697, "output_tokens": 2306, "total_tokens": 5003, "input_cost_usd": 0.00013485000000000003, "output_cost_usd": 0.0009224, "estimated_cost_usd": 0.00105725}, "duration": 19.688917636871338, "timestamp": "2026-03-23T19:41:11.365773", "parsed": {"metadata": {"send_date": ["1926-06-22"], "letter_title": ["null"], "sender_persons": ["Basler Schiffahrt-Aktiengesellschaft"], "receiver_persons": ["Herrn P. Christ - Wackernagel"], "document_number": "letter07"}}, "conversation_id": "3e0e8f2c-12cb-428b-9fd7-b350198f8252", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-DMeUoRI6qfkF37LW0XP4RVgeS7i0h\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1926-06-22\\\"],\\\"letter_title\\\":[\\\"null\\\"],\\\"sender_persons\\\":[\\\"Basler Schiffahrt-Aktiengesellschaft\\\"],\\\"receiver_persons\\\":[\\\"Herrn P. Christ - Wackernagel\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1926-06-22\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"Basler Schiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Herrn P. Christ - Wackernagel\"]}}}}],\"created\":1774291254,\"model\":\"gpt-5-nano-2025-08-07\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":2306,\"prompt_tokens\":2697,\"total_tokens\":5003,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":2240,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.51, "f1_micro": 0.53, "cost_summary": {"total_input_tokens": 244298, "total_output_tokens": 143144, "total_tokens": 387442, "input_cost_usd": 0.012214900000000011, "output_cost_usd": 0.05725759999999999, "total_cost_usd": 0.0694725}}, "normalized_score": 51.0}, {"_id": {"$oid": "69d4eb12b877594bc5718cfc"}, "test_id": "T0719", "benchmark": "business_letters", "date": "2026-03-23", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "x-ai", "model": "grok-4.20-0309-reasoning", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-09-28\"],\"letter_title\":null,\"sender_persons\":[\"Jeanneret\"],\"receiver_persons\":[\"Max Vischer\"]}}", "model": "grok-4.20-0309-reasoning", "provider": "x-ai", "finish_reason": "stop", "usage": {"input_tokens": 815, "output_tokens": 51, "total_tokens": 3435, "cached_tokens": 576, "input_cost_usd": 0.00163, "output_cost_usd": 0.000306, "estimated_cost_usd": 0.001936}, "duration": 26.252490758895874, "timestamp": "2026-03-23T13:55:13.611134", "parsed": {"metadata": {"send_date": ["1926-09-28"], "letter_title": null, "sender_persons": ["Jeanneret"], "receiver_persons": ["Max Vischer"], "document_number": "letter45"}}, "conversation_id": "8924270b-31d7-441c-9f49-1d151c3d4b51", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 1, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"7156668c-3fc4-987a-a65d-e79d8dbbb3de\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1926-09-28\\\"],\\n \\\"letter_title\\\": null,\\n \\\"sender_persons\\\": [\\\"Jeanneret\\\"],\\n \\\"receiver_persons\\\": [\\\"Max Vischer\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1926-09-28\"],\"letter_title\":null,\"sender_persons\":[\"Jeanneret\"],\"receiver_persons\":[\"Max Vischer\"]}}}}],\"created\":1774270513,\"model\":\"grok-4.20-0309-reasoning\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":\"fp_d6e36c82c2\",\"usage\":{\"completion_tokens\":51,\"prompt_tokens\":815,\"total_tokens\":3435,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":2569,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":576,\"text_tokens\":623,\"image_tokens\":192},\"num_sources_used\":0,\"cost_in_usd_ticks\":163132000}}"}, "scoring": {"f1_macro": 0.22, "f1_micro": 0.2, "cost_summary": {"total_input_tokens": 54409, "total_output_tokens": 3144, "total_tokens": 57553, "input_cost_usd": 0.10881800000000014, "output_cost_usd": 0.018863999999999995, "total_cost_usd": 0.127682}}, "normalized_score": 22.0}, {"_id": {"$oid": "69d4eb12b877594bc5718ce1"}, "test_id": "T0060", "benchmark": "business_letters", "date": "2026-03-23", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "pixtral-large-2411", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\n \"metadata\": {\n \"letter_title\": [null],\n \"send_date\": [null],\n \"sender_persons\": [null],\n \"receiver_persons\": [null]\n }\n}", "model": "pixtral-large-2411", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 640, "output_tokens": 56, "total_tokens": 696, "input_cost_usd": 0.00128, "output_cost_usd": 0.000336, "estimated_cost_usd": 0.001616}, "duration": 1.9846034049987793, "timestamp": "2026-03-23T14:51:09.143800", "parsed": {"metadata": {"letter_title": [null], "send_date": [null], "sender_persons": [null], "receiver_persons": [null], "document_number": "letter15"}}, "conversation_id": "df1d44dc-53f0-4458-8354-b70253f88d4c", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"4a30e66c003c47829a5f499f75763a60\",\"object\":\"chat.completion\",\"model\":\"pixtral-large-2411\",\"usage\":{\"prompt_tokens\":640,\"completion_tokens\":56,\"total_tokens\":696,\"prompt_tokens_details\":{\"cached_tokens\":0}},\"created\":1774273868,\"choices\":[{\"index\":0,\"message\":{\"role\":\"assistant\",\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [null],\\n \\\"send_date\\\": [null],\\n \\\"sender_persons\\\": [null],\\n \\\"receiver_persons\\\": [null]\\n }\\n}\",\"tool_calls\":null,\"prefix\":false},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 16000, "total_output_tokens": 1536, "total_tokens": 17536, "input_cost_usd": 0.032, "output_cost_usd": 0.009216000000000002, "total_cost_usd": 0.041215999999999996}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718d25"}, "test_id": "T0696", "benchmark": "business_letters", "date": "2026-03-23", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5.3-codex", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true, \"api_style\":\"responses\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1927-09-15\"],\"letter_title\":null,\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Herr Rupprecht\"]}}", "model": "gpt-5.3-codex", "provider": "openai", "finish_reason": "completed", "usage": {"input_tokens": 4094, "output_tokens": 50, "total_tokens": 4144, "input_cost_usd": 0.007164500000000001, "output_cost_usd": 0.0007, "estimated_cost_usd": 0.0078645}, "duration": 3.5335521697998047, "timestamp": "2026-03-23T21:13:41.724420", "parsed": {"metadata": {"send_date": ["1927-09-15"], "letter_title": null, "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Herr Rupprecht"], "document_number": "letter13"}}, "conversation_id": "0a5a66ae-b3b0-4d13-bbf1-d0e137df4dc9", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"resp_0b0af8baa2961a640069c19ef4051c8193becb5eacdd928176\",\"created_at\":1774296820.0,\"error\":null,\"incomplete_details\":null,\"instructions\":\"You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history\",\"metadata\":{},\"model\":\"gpt-5.3-codex\",\"object\":\"response\",\"output\":[{\"id\":\"msg_0b0af8baa2961a640069c19ef5032881938cf727984185de9d\",\"content\":[{\"annotations\":[],\"text\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1927-09-15\\\"],\\\"letter_title\\\":null,\\\"sender_persons\\\":[\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"],\\\"receiver_persons\\\":[\\\"Herr Rupprecht\\\"]}}\",\"type\":\"output_text\",\"logprobs\":[]}],\"role\":\"assistant\",\"status\":\"completed\",\"type\":\"message\",\"phase\":\"final_answer\"}],\"parallel_tool_calls\":true,\"temperature\":0.0,\"tool_choice\":\"auto\",\"tools\":[],\"top_p\":0.98,\"background\":false,\"completed_at\":1774296821.0,\"conversation\":null,\"max_output_tokens\":null,\"max_tool_calls\":null,\"previous_response_id\":null,\"prompt\":null,\"prompt_cache_key\":null,\"prompt_cache_retention\":null,\"reasoning\":{\"effort\":\"none\",\"generate_summary\":null,\"summary\":null},\"safety_identifier\":null,\"service_tier\":\"default\",\"status\":\"completed\",\"text\":{\"format\":{\"type\":\"text\"},\"verbosity\":\"medium\"},\"top_logprobs\":0,\"truncation\":\"disabled\",\"usage\":{\"input_tokens\":4094,\"input_tokens_details\":{\"cached_tokens\":0},\"output_tokens\":50,\"output_tokens_details\":{\"reasoning_tokens\":0},\"total_tokens\":4144},\"user\":null,\"billing\":{\"payer\":\"developer\"},\"frequency_penalty\":0.0,\"presence_penalty\":0.0,\"store\":true}"}, "scoring": {"f1_macro": 0.6, "f1_micro": 0.54, "cost_summary": {"total_input_tokens": 129241, "total_output_tokens": 1915, "total_tokens": 131156, "input_cost_usd": 0.22617174999999998, "output_cost_usd": 0.02680999999999999, "total_cost_usd": 0.25298175}}, "normalized_score": 60.0}, {"_id": {"$oid": "69d4eb12b877594bc5718d06"}, "test_id": "T0695", "benchmark": "business_letters", "date": "2026-03-23", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5.3-codex", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false, \"api_style\":\"responses\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\n \"metadata\": {\n \"send_date\": [\"1932-09-23\"],\n \"letter_title\": null,\n \"sender_persons\": null,\n \"receiver_persons\": [\"Basler Rheinschiffahrts-Aktiengesellschaft Direktion\"]\n }\n}", "model": "gpt-5.3-codex", "provider": "openai", "finish_reason": "completed", "usage": {"input_tokens": 2327, "output_tokens": 63, "total_tokens": 2390, "input_cost_usd": 0.00407225, "output_cost_usd": 0.000882, "estimated_cost_usd": 0.00495425}, "duration": 2.105715751647949, "timestamp": "2026-03-23T21:13:36.393714", "parsed": {"metadata": {"send_date": ["1932-09-23"], "letter_title": null, "sender_persons": null, "receiver_persons": ["Basler Rheinschiffahrts-Aktiengesellschaft Direktion"], "document_number": "letter51"}}, "conversation_id": "0ec89113-0dc8-4537-ba1c-bf66cfcd400b", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"resp_069a2707370b91a70069c19eef38288197a148a86a23b722fa\",\"created_at\":1774296815.0,\"error\":null,\"incomplete_details\":null,\"instructions\":\"You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history\",\"metadata\":{},\"model\":\"gpt-5.3-codex\",\"object\":\"response\",\"output\":[{\"id\":\"msg_069a2707370b91a70069c19eefda148197b13a24a1095c9c89\",\"content\":[{\"annotations\":[],\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1932-09-23\\\"],\\n \\\"letter_title\\\": null,\\n \\\"sender_persons\\\": null,\\n \\\"receiver_persons\\\": [\\\"Basler Rheinschiffahrts-Aktiengesellschaft Direktion\\\"]\\n }\\n}\",\"type\":\"output_text\",\"logprobs\":[]}],\"role\":\"assistant\",\"status\":\"completed\",\"type\":\"message\",\"phase\":\"final_answer\"}],\"parallel_tool_calls\":true,\"temperature\":0.0,\"tool_choice\":\"auto\",\"tools\":[],\"top_p\":0.98,\"background\":false,\"completed_at\":1774296816.0,\"conversation\":null,\"max_output_tokens\":null,\"max_tool_calls\":null,\"previous_response_id\":null,\"prompt\":null,\"prompt_cache_key\":null,\"prompt_cache_retention\":null,\"reasoning\":{\"effort\":\"none\",\"generate_summary\":null,\"summary\":null},\"safety_identifier\":null,\"service_tier\":\"default\",\"status\":\"completed\",\"text\":{\"format\":{\"type\":\"text\"},\"verbosity\":\"medium\"},\"top_logprobs\":0,\"truncation\":\"disabled\",\"usage\":{\"input_tokens\":2327,\"input_tokens_details\":{\"cached_tokens\":0},\"output_tokens\":63,\"output_tokens_details\":{\"reasoning_tokens\":0},\"total_tokens\":2390},\"user\":null,\"billing\":{\"payer\":\"developer\"},\"frequency_penalty\":0.0,\"presence_penalty\":0.0,\"store\":true}"}, "scoring": {"f1_macro": 0.51, "f1_micro": 0.63, "cost_summary": {"total_input_tokens": 75845, "total_output_tokens": 1452, "total_tokens": 77297, "input_cost_usd": 0.13272875, "output_cost_usd": 0.020328000000000002, "total_cost_usd": 0.15305675}}, "normalized_score": 51.0}, {"_id": {"$oid": "69d4eb12b877594bc5718cf7"}, "test_id": "T0721", "benchmark": "business_letters", "date": "2026-03-23", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "x-ai", "model": "grok-4.20-0309-reasoning", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1956-06-22\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":[\"P. Christ - Wackernagel\"]}}", "model": "grok-4.20-0309-reasoning", "provider": "x-ai", "finish_reason": "stop", "usage": {"input_tokens": 815, "output_tokens": 53, "total_tokens": 3248, "cached_tokens": 768, "input_cost_usd": 0.00163, "output_cost_usd": 0.00031800000000000003, "estimated_cost_usd": 0.001948}, "duration": 25.486347436904907, "timestamp": "2026-03-23T13:57:07.132795", "parsed": {"metadata": {"send_date": ["1956-06-22"], "letter_title": null, "sender_persons": null, "receiver_persons": ["P. Christ - Wackernagel"], "document_number": "letter07"}}, "conversation_id": "0b53b101-dae9-4edc-b260-0dd5668e7f1c", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"7d35dec8-8c46-91a5-80f8-ccaaff08f163\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1956-06-22\\\"],\\n \\\"letter_title\\\": null,\\n \\\"sender_persons\\\": null,\\n \\\"receiver_persons\\\": [\\\"P. Christ - Wackernagel\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1956-06-22\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":[\"P. Christ - Wackernagel\"]}}}}],\"created\":1774270626,\"model\":\"grok-4.20-0309-reasoning\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":\"fp_d6e36c82c2\",\"usage\":{\"completion_tokens\":53,\"prompt_tokens\":815,\"total_tokens\":3248,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":2380,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":768,\"text_tokens\":623,\"image_tokens\":192},\"num_sources_used\":0,\"cost_in_usd_ticks\":151356000}}"}, "scoring": {"f1_macro": 0.28, "f1_micro": 0.25, "cost_summary": {"total_input_tokens": 32094, "total_output_tokens": 1873, "total_tokens": 33967, "input_cost_usd": 0.064188, "output_cost_usd": 0.011237999999999998, "total_cost_usd": 0.07542599999999999}}, "normalized_score": 28.000000000000004}, {"_id": {"$oid": "69d4eb12b877594bc5718cd4"}, "test_id": "T0696", "benchmark": "business_letters", "date": "2026-03-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5.3-codex", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true, \"api_style\":\"responses\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1927-09-15\"],\"letter_title\":null,\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Herr Rupprecht\"]}}", "model": "gpt-5.3-codex", "provider": "openai", "finish_reason": "completed", "usage": {"input_tokens": 4094, "output_tokens": 50, "total_tokens": 4144, "input_cost_usd": 0.007164500000000001, "output_cost_usd": 0.0007, "estimated_cost_usd": 0.0078645}, "duration": 3.637359857559204, "timestamp": "2026-03-17T22:45:24.530196", "parsed": {"metadata": {"send_date": ["1927-09-15"], "letter_title": null, "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Herr Rupprecht"], "document_number": "letter13"}}, "conversation_id": "8e4e912d-e955-4bd6-b725-9780fb67da65", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"resp_09c50f425c1645dd0069b9cb70aa288194b53db377cb6d1a54\",\"created_at\":1773783920.0,\"error\":null,\"incomplete_details\":null,\"instructions\":\"You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history\",\"metadata\":{},\"model\":\"gpt-5.3-codex\",\"object\":\"response\",\"output\":[{\"id\":\"msg_09c50f425c1645dd0069b9cb7204cc81949849d235396edfa3\",\"content\":[{\"annotations\":[],\"text\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1927-09-15\\\"],\\\"letter_title\\\":null,\\\"sender_persons\\\":[\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"],\\\"receiver_persons\\\":[\\\"Herr Rupprecht\\\"]}}\",\"type\":\"output_text\",\"logprobs\":[]}],\"role\":\"assistant\",\"status\":\"completed\",\"type\":\"message\",\"phase\":\"final_answer\"}],\"parallel_tool_calls\":true,\"temperature\":0.0,\"tool_choice\":\"auto\",\"tools\":[],\"top_p\":0.98,\"background\":false,\"completed_at\":1773783922.0,\"conversation\":null,\"max_output_tokens\":null,\"max_tool_calls\":null,\"previous_response_id\":null,\"prompt\":null,\"prompt_cache_key\":null,\"prompt_cache_retention\":null,\"reasoning\":{\"effort\":\"none\",\"generate_summary\":null,\"summary\":null},\"safety_identifier\":null,\"service_tier\":\"default\",\"status\":\"completed\",\"text\":{\"format\":{\"type\":\"text\"},\"verbosity\":\"medium\"},\"top_logprobs\":0,\"truncation\":\"disabled\",\"usage\":{\"input_tokens\":4094,\"input_tokens_details\":{\"cached_tokens\":0},\"output_tokens\":50,\"output_tokens_details\":{\"reasoning_tokens\":0},\"total_tokens\":4144},\"user\":null,\"billing\":{\"payer\":\"developer\"},\"frequency_penalty\":0.0,\"presence_penalty\":0.0,\"store\":true}"}, "scoring": {"f1_macro": 0.6, "f1_micro": 0.54, "cost_summary": {"total_input_tokens": 129241, "total_output_tokens": 1887, "total_tokens": 131128, "input_cost_usd": 0.22617174999999998, "output_cost_usd": 0.026417999999999994, "total_cost_usd": 0.25258975}}, "normalized_score": 60.0}, {"_id": {"$oid": "69d4eb12b877594bc5718ccc"}, "test_id": "T0695", "benchmark": "business_letters", "date": "2026-03-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5.3-codex", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false, \"api_style\":\"responses\"}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-09-23\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":[\"Basler Rheinschiffahrts-Aktiengesellschaft Direktion\"]}}", "model": "gpt-5.3-codex", "provider": "openai", "finish_reason": "completed", "usage": {"input_tokens": 2327, "output_tokens": 49, "total_tokens": 2376, "input_cost_usd": 0.00407225, "output_cost_usd": 0.000686, "estimated_cost_usd": 0.00475825}, "duration": 2.2546579837799072, "timestamp": "2026-03-17T22:45:20.280806", "parsed": {"metadata": {"send_date": ["1932-09-23"], "letter_title": null, "sender_persons": null, "receiver_persons": ["Basler Rheinschiffahrts-Aktiengesellschaft Direktion"], "document_number": "letter51"}}, "conversation_id": "5d1ef4d7-bbd7-4194-88d0-761f9e236df2", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"resp_0445d41b696eb9c50069b9cb6d04bc819589e34d55bd5940c1\",\"created_at\":1773783917.0,\"error\":null,\"incomplete_details\":null,\"instructions\":\"You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history\",\"metadata\":{},\"model\":\"gpt-5.3-codex\",\"object\":\"response\",\"output\":[{\"id\":\"msg_0445d41b696eb9c50069b9cb6dd3c081959dc67eb9479efa63\",\"content\":[{\"annotations\":[],\"text\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1932-09-23\\\"],\\\"letter_title\\\":null,\\\"sender_persons\\\":null,\\\"receiver_persons\\\":[\\\"Basler Rheinschiffahrts-Aktiengesellschaft Direktion\\\"]}}\",\"type\":\"output_text\",\"logprobs\":[]}],\"role\":\"assistant\",\"status\":\"completed\",\"type\":\"message\",\"phase\":\"final_answer\"}],\"parallel_tool_calls\":true,\"temperature\":0.0,\"tool_choice\":\"auto\",\"tools\":[],\"top_p\":0.98,\"background\":false,\"completed_at\":1773783918.0,\"conversation\":null,\"max_output_tokens\":null,\"max_tool_calls\":null,\"previous_response_id\":null,\"prompt\":null,\"prompt_cache_key\":null,\"prompt_cache_retention\":null,\"reasoning\":{\"effort\":\"none\",\"generate_summary\":null,\"summary\":null},\"safety_identifier\":null,\"service_tier\":\"default\",\"status\":\"completed\",\"text\":{\"format\":{\"type\":\"text\"},\"verbosity\":\"medium\"},\"top_logprobs\":0,\"truncation\":\"disabled\",\"usage\":{\"input_tokens\":2327,\"input_tokens_details\":{\"cached_tokens\":0},\"output_tokens\":49,\"output_tokens_details\":{\"reasoning_tokens\":0},\"total_tokens\":2376},\"user\":null,\"billing\":{\"payer\":\"developer\"},\"frequency_penalty\":0.0,\"presence_penalty\":0.0,\"store\":true}"}, "scoring": {"f1_macro": 0.5, "f1_micro": 0.6, "cost_summary": {"total_input_tokens": 75845, "total_output_tokens": 1373, "total_tokens": 77218, "input_cost_usd": 0.13272875, "output_cost_usd": 0.019222000000000003, "total_cost_usd": 0.15195075}}, "normalized_score": 50.0}, {"_id": {"$oid": "69d4eb12b877594bc5718cb3"}, "test_id": "T0643", "benchmark": "business_letters", "date": "2026-03-16", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-sonnet-4-6", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\": {\"send_date\": [\"1925-06-28\"], \"letter_title\": [null], \"sender_persons\": [\"Max Vischer\"], \"receiver_persons\": [\"P. Christ-Wackernagel\"]}}", "model": "claude-sonnet-4-6", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 4342, "output_tokens": 81, "total_tokens": 4423, "input_cost_usd": 0.013026000000000001, "output_cost_usd": 0.0012150000000000002, "estimated_cost_usd": 0.014241000000000002}, "duration": 4.425912618637085, "timestamp": "2026-03-16T15:50:13.402736", "parsed": {"metadata": {"send_date": ["1925-06-28"], "letter_title": [null], "sender_persons": ["Max Vischer"], "receiver_persons": ["P. Christ-Wackernagel"], "document_number": "letter09"}}, "conversation_id": "adb23fb0-8047-4167-9da1-219a276cc46b", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 1, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"msg_0156PozMtE7WZRYnBudnope9\",\"content\":[{\"id\":\"toolu_01AZYoCSm2hoW2vM4tq9xkbG\",\"input\":{\"metadata\":{\"send_date\":[\"1925-06-28\"],\"letter_title\":[null],\"sender_persons\":[\"Max Vischer\"],\"receiver_persons\":[\"P. Christ-Wackernagel\"],\"document_number\":\"letter09\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\",\"caller\":{\"type\":\"direct\"}}],\"model\":\"claude-sonnet-4-6\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"inference_geo\":\"global\",\"input_tokens\":4342,\"output_tokens\":81,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.59, "f1_micro": 0.54, "cost_summary": {"total_input_tokens": 137390, "total_output_tokens": 3045, "total_tokens": 140435, "input_cost_usd": 0.4121699999999998, "output_cost_usd": 0.045675, "total_cost_usd": 0.4578450000000001}}, "normalized_score": 59.0}, {"_id": {"$oid": "69d4eb12b877594bc5718cb4"}, "test_id": "T0672", "benchmark": "business_letters", "date": "2026-03-16", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-3.1-flash-lite-preview", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-03-24\"],\"letter_title\":[\"\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"P. Christ-Wackernagel\"]}}", "model": "gemini-3.1-flash-lite-preview", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 1428, "output_tokens": 77, "total_tokens": 1505, "input_cost_usd": 0.000357, "output_cost_usd": 0.0001155, "estimated_cost_usd": 0.0004725}, "duration": 2.0239663124084473, "timestamp": "2026-03-16T19:08:24.496424", "parsed": {"metadata": {"send_date": ["1926-03-24"], "letter_title": [""], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["P. Christ-Wackernagel"], "document_number": "letter03"}}, "conversation_id": "3f3c3d84-ca7d-4e20-803d-750937f1ed65", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Mon, 16 Mar 2026 18:08:31 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=1495\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"media_resolution\":null,\"code_execution_result\":null,\"executable_code\":null,\"file_data\":null,\"function_call\":null,\"function_response\":null,\"inline_data\":null,\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1926-03-24\\\"],\\n \\\"letter_title\\\": [\\\"\\\"],\\n \\\"sender_persons\\\": [\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"],\\n \\\"receiver_persons\\\": [\\\"P. Christ-Wackernagel\\\"]\\n }\\n}\",\"thought\":null,\"thought_signature\":\"EjQKMgG-Pvb76TWyYZHlUtSB23SIF0uZYpN2X-ttcMDyprwq_UqxSV801RErDpATsL-8gEH4\",\"video_metadata\":null}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null,\"url_context_metadata\":null}],\"create_time\":null,\"model_version\":\"gemini-3.1-flash-lite-preview\",\"prompt_feedback\":null,\"response_id\":\"H0e4aejKEYCW28oPw4-7uQo\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":77,\"candidates_tokens_details\":null,\"prompt_token_count\":1428,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":336},{\"modality\":\"IMAGE\",\"token_count\":1092}],\"thoughts_token_count\":null,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":1505,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1926-03-24\"],\"letter_title\":[\"\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"P. Christ-Wackernagel\"]}}}"}, "scoring": {"f1_macro": 0.59, "f1_micro": 0.54, "cost_summary": {"total_input_tokens": 79548, "total_output_tokens": 2592, "total_tokens": 82140, "input_cost_usd": 0.019886999999999995, "output_cost_usd": 0.003888000000000001, "total_cost_usd": 0.023774999999999998}}, "normalized_score": 59.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c9b"}, "test_id": "T0631", "benchmark": "business_letters", "date": "2026-03-16", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-opus-4-6", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-03-24\"],\"letter_title\":null,\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"P. Christ-Wackernagel\"]}}", "model": "claude-opus-4-6", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 2788, "output_tokens": 103, "total_tokens": 2891, "input_cost_usd": 0.013940000000000001, "output_cost_usd": 0.002575, "estimated_cost_usd": 0.016515000000000002}, "duration": 5.237056255340576, "timestamp": "2026-03-16T15:50:16.268759", "parsed": {"metadata": {"send_date": ["1926-03-24"], "letter_title": null, "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["P. Christ-Wackernagel"], "document_number": "letter03"}}, "conversation_id": "e89be632-1660-4569-ab80-72c584630773", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"msg_01KaRfFC5WMLqCE3uDL3qZsY\",\"content\":[{\"id\":\"toolu_01NhzzaE2AAqdPVtdkgRPQeC\",\"input\":{\"metadata\":{\"send_date\":[\"1926-03-24\"],\"letter_title\":null,\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"P. Christ-Wackernagel\"],\"document_number\":\"letter03\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\",\"caller\":{\"type\":\"direct\"}}],\"model\":\"claude-opus-4-6\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"inference_geo\":\"global\",\"input_tokens\":2788,\"output_tokens\":103,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.63, "f1_micro": 0.57, "cost_summary": {"total_input_tokens": 137390, "total_output_tokens": 3019, "total_tokens": 140409, "input_cost_usd": 0.6869499999999998, "output_cost_usd": 0.075475, "total_cost_usd": 0.7624250000000001}}, "normalized_score": 63.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c89"}, "test_id": "T0655", "benchmark": "business_letters", "date": "2026-03-16", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5.4-2026-03-05", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-03-26\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"W. W. Braun\"],\"receiver_persons\":[\"Herr Christ\"]}}", "model": "gpt-5.4-2026-03-05", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 3262, "output_tokens": 46, "total_tokens": 3308, "cached_tokens": 2816, "input_cost_usd": 0.008155, "output_cost_usd": 0.00069, "estimated_cost_usd": 0.008845}, "duration": 3.045013189315796, "timestamp": "2026-03-16T17:06:00.400492", "parsed": {"metadata": {"send_date": ["1926-03-26"], "letter_title": ["null"], "sender_persons": ["W. W. Braun"], "receiver_persons": ["Herr Christ"], "document_number": "letter04"}}, "conversation_id": "67f2772a-8455-4304-b852-f8823f58c74c", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 1, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-DK4k9SRZyuI70lsTneN93Bp7ek9dx\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1926-03-26\\\"],\\\"letter_title\\\":[\\\"null\\\"],\\\"sender_persons\\\":[\\\"W. W. Braun\\\"],\\\"receiver_persons\\\":[\\\"Herr Christ\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1926-03-26\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"W. W. Braun\"],\"receiver_persons\":[\"Herr Christ\"]}}}}],\"created\":1773677165,\"model\":\"gpt-5.4-2026-03-05\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":46,\"prompt_tokens\":3262,\"total_tokens\":3308,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":2816}}}"}, "scoring": {"f1_macro": 0.62, "f1_micro": 0.55, "cost_summary": {"total_input_tokens": 190378, "total_output_tokens": 1898, "total_tokens": 192276, "input_cost_usd": 0.47594500000000023, "output_cost_usd": 0.02847, "total_cost_usd": 0.504415}}, "normalized_score": 62.0}, {"_id": {"$oid": "69d4eb12b877594bc5718cbf"}, "test_id": "T0683", "benchmark": "business_letters", "date": "2026-03-16", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-3.1-pro-preview", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-08-13\"],\"letter_title\":null,\"sender_persons\":[\"Groschopf\",\"J.A. Ritter\"],\"receiver_persons\":[\"Dr. Max Vischer\"]}}", "model": "gemini-3.1-pro-preview", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 3612, "output_tokens": 94, "total_tokens": 4327, "input_cost_usd": 0.007224, "output_cost_usd": 0.0011279999999999999, "estimated_cost_usd": 0.008352}, "duration": 8.71237564086914, "timestamp": "2026-03-16T19:17:00.083746", "parsed": {"metadata": {"send_date": ["1926-08-13"], "letter_title": null, "sender_persons": ["Groschopf", "J.A. Ritter"], "receiver_persons": ["Dr. Max Vischer"], "document_number": "letter12"}}, "conversation_id": "70f205f3-c2ad-4f2d-9b73-928e3abb57ff", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 2, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Mon, 16 Mar 2026 18:17:06 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=7881\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"media_resolution\":null,\"code_execution_result\":null,\"executable_code\":null,\"file_data\":null,\"function_call\":null,\"function_response\":null,\"inline_data\":null,\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1926-08-13\\\"\\n ],\\n \\\"letter_title\\\": null,\\n \\\"sender_persons\\\": [\\n \\\"Groschopf\\\",\\n \\\"J.A. Ritter\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Dr. Max Vischer\\\"\\n ]\\n }\\n}\",\"thought\":null,\"thought_signature\":\"ErIOCq8OAb4-9vsT7P331IVAdVw_RKJzm13ThI_2QB3UbtLxyGqErghEBh4l2Qo4u3RVC4Sdw_rlgV47_hFgQEHtbDdlBvgqHtxjPCtTnyK_XcpaaWfMCLxqJKhn3YkxL1dWdJ7D3PFPyj4S0AFzL3fMJAAeQm3kEHZsaO5uMtS-iJjqLgcl_wPZCX_fWUMt2rqzZbudP4YV6xSvhRbXVfluOk87QbkXSNlyKZWbtr0vzvrNBMRBqLhcJEeIMn6t9yZzDogip96FgD6R9DzEdUTJUivhOIDbAbI0-XyV_41AQDISBO9QmdDOrryhcoaHMSMrnpE7m-wq1E50Jn1-IipelcCN8XSNsdTdCSmk9g0leUGFOR2kTVx-ol76Stwkc-nml_-807z0LEReHOK5itojxhesdknyPzNCeVixbPgabt8QSRkdX73z4xYBr_gvY-3yhv4PqFYr1IZGAOJMXX8nwMs_d9uvL_84Y8mpLmPbqHv0zjztze7GDfbjqukgIIQGTvHsjZRTwAjP_0PmPUu3_5VczAEWI5tDi-COASRlKEp5P-vpBSb3e3KzT5ZcqvK909NUynuxZvOQ_jFtwUCLGN_GXDZzofLlOnbN131OtcuQ0-dSGCZwkSScua6I1eXJL6cgBh4jG2TWlhEQocIKAhMp7bikxs4a8RN_93O5CwurD9DmoR8EjvXVic4kNlIp3SmAxUa1se00OOXrhUjnZKiqr77pVIXjf4Qb0squ7mJRAVp7BVzBdAVakeRc7SekGmQknadyxA8ySTh81gYvKX0m0A0HatThCakebSXsSTHmyHQ2Oj11hfkeMj0qRWDbVv0sffj5xtu9hpzwxbXU5X9bKqSs5N0_mchlMvz2cSdZjG16Bryc4t6hnKBo45vVp2xTNLQhOWEvhBeSaLqn9ShIEaN_9ffZWLCP1X_K8ZmrIymCTie9LNxnL0RQFAPLbp864sV393pFATFD4KIH890upW6gSjpGYa3QxYdht18wLzOpF7EV20sOBKo_AO6sM7FzvjnxQz4pb_Y0iA138twhm3JVrdIgRm0wp4eifFjjUcf51izUOEOPd-r-fo19IveDthb0_28fq9NwVAz_zEhjKFHpBcTu3vQ96WXbApjU4GPyvX3GzDyB04XwAT_T2WBGT5NbePvFc3rmRM__cPT3L_yTO0U98TuNY0Htcn5qZrBNfJwWm-ITrNv3j5p79CPqi9cdZLow_tuhQDywYoMWwiYC_S4A2rK8gXnR54oMoQQaBTFudbga-9aiojzso3M_0z5JQXNdVS64fR0CwWJ3HcI9Jf1qd9NUc0VZHTV2YBWs9MklwiRWaZja1KKwkEwarz5GlZFMFQjIPdvdeoHsnw1ir45Tnt-25ziP4XdZd_ab0d0Ddb4T3C36Tnu-g4nkSWWxFPUbXQwWr4b-bQSdhPIcUf3IjjS6ykYO8A64D23cH_Xl5CLG7e8aVQOBbIaOUwgvLGysqiRMoPJRTfKzHBZPFeL6ybd9LPrH44ApPMokJ1D_kmjwzo5X2I5cDUzwKFx8zBQ9Eb-mCDjL93iuTbhWGUq0409uy7FSmO7fYbda6EkjK1CCOTTL3fONmPURuQbvop8slZh68zyGb2VMgwOWuCZ3AABFOT3qUxrYKQ5xw0f3YnMyvRW_oQmw4sNIT0evGXaFnkc3UcHqviNu1F_IZAiHFZgKPbeYbCeo9BvjSXMpJdLEzcOasTwp23nqsfzMu69fQAjlhATpzIXzhn1P_zRDewKZNT-JJVG0-CkFUSi1FmY6zoIiJ2XMk25NqiCVBeHCjIO2mCQLhR58by3L52BFjFnfLw4PMVq3GBviFkTBGslmNHAN_0N_VshY36KR3qayAXjibcGM2oqZJ0Msk1amuayIsfDlt7l4SVS9lma-aidolZ0EGNYEv4YnfXoRuKqbsnveq1HgeJ4HNjOGnT6TF5SVELy7LHzX0J5QZ9kHJJMc_0W7wEoS_I0KnFfXpF5iF33vVE8UlThgNkm9CJhoSWFl8tlbs8_2asPPQ2IlRmaJ4e6IjkgBFGhFRu3TOzmWj0dbK1Ie768DT-f7oXamrsVNK6Qigg5f7IycGWhQA_dpEA5U5X6kQ6m_ivU-tyd73wW5LOnfpXg4xDOGX3_KzdaS4RX6lg8PMLVGgZQ2KWWmg-VIU92eVsTpHuJkMhsNks-LOsox-FF0ygAEXqmJkLfzrQQ9vGoGk1AkXR9EUrcV684hcp8_iZ_DrQhhwi64_mw57VKXM49KBDHwcHm4rLfUClvR3fciGpbnb5a4Yp1dbZA2S1wln5mGjbB67GOnPR0huCTiMBajCiub82TDyYqplK4g1gqRFDGS-yTZtWJrW7v8O5TCKMQ0rAc6Wlfem2xlGOEj2qbdPG0puRrgb7yoIdDBHw4qD93LQgs-b55jCid5Qk_4vdyWxx65Npe4GbOPSLWZ4BBY\",\"video_metadata\":null}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null,\"url_context_metadata\":null}],\"create_time\":null,\"model_version\":\"gemini-3.1-pro-preview\",\"prompt_feedback\":null,\"response_id\":\"Ikm4abPzNp-VnsEPqJznuAI\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":94,\"candidates_tokens_details\":null,\"prompt_token_count\":3612,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":336},{\"modality\":\"IMAGE\",\"token_count\":3276}],\"thoughts_token_count\":621,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":4327,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1926-08-13\"],\"letter_title\":null,\"sender_persons\":[\"Groschopf\",\"J.A. Ritter\"],\"receiver_persons\":[\"Dr. Max Vischer\"]}}}"}, "scoring": {"f1_macro": 0.72, "f1_micro": 0.83, "cost_summary": {"total_input_tokens": 46620, "total_output_tokens": 1406, "total_tokens": 48026, "input_cost_usd": 0.09323999999999999, "output_cost_usd": 0.016871999999999998, "total_cost_usd": 0.11011200000000003}}, "normalized_score": 72.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c85"}, "test_id": "T0682", "benchmark": "business_letters", "date": "2026-03-16", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-3.1-pro-preview", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-12-19\"],\"letter_title\":[\"Betr. Personenschiffahrt\"],\"sender_persons\":null,\"receiver_persons\":[\"M. Vischer - von Planta\"]}}", "model": "gemini-3.1-pro-preview", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 1428, "output_tokens": 56, "total_tokens": 1484, "input_cost_usd": 0.002856, "output_cost_usd": 0.000672, "estimated_cost_usd": 0.003528}, "duration": 2.544675588607788, "timestamp": "2026-03-16T19:09:14.526031", "parsed": {"metadata": {"send_date": ["1932-12-19"], "letter_title": ["Betr. Personenschiffahrt"], "sender_persons": null, "receiver_persons": ["M. Vischer - von Planta"], "document_number": "letter60"}}, "conversation_id": "7180db24-3059-47fb-b06f-621e329af201", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 1}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Mon, 16 Mar 2026 18:09:21 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=2388\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"media_resolution\":null,\"code_execution_result\":null,\"executable_code\":null,\"file_data\":null,\"function_call\":null,\"function_response\":null,\"inline_data\":null,\"text\":\"{\\\"metadata\\\": {\\\"send_date\\\": [\\\"1932-12-19\\\"], \\\"letter_title\\\": [\\\"Betr. Personenschiffahrt\\\"], \\\"sender_persons\\\": null, \\\"receiver_persons\\\": [\\\"M. Vischer - von Planta\\\"]}}\",\"thought\":null,\"thought_signature\":\"EjQKMgG-Pvb7nJLO__NhHPyDmYdwxH3aVWBcvl_5UzeDhL2BIR2BGY1L6WjyRLURz27O8rh7\",\"video_metadata\":null}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null,\"url_context_metadata\":null}],\"create_time\":null,\"model_version\":\"gemini-3.1-pro-preview\",\"prompt_feedback\":null,\"response_id\":\"UUe4aba8EvyP28oPgPGi8Ac\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":56,\"candidates_tokens_details\":null,\"prompt_token_count\":1428,\"prompt_tokens_details\":[{\"modality\":\"IMAGE\",\"token_count\":1092},{\"modality\":\"TEXT\",\"token_count\":336}],\"thoughts_token_count\":null,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":1484,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1932-12-19\"],\"letter_title\":[\"Betr. Personenschiffahrt\"],\"sender_persons\":null,\"receiver_persons\":[\"M. Vischer - von Planta\"]}}}"}, "scoring": {"f1_macro": 0.63, "f1_micro": 0.66, "cost_summary": {"total_input_tokens": 126168, "total_output_tokens": 3862, "total_tokens": 130030, "input_cost_usd": 0.25233599999999984, "output_cost_usd": 0.04634399999999999, "total_cost_usd": 0.29868000000000006}}, "normalized_score": 63.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c95"}, "test_id": "T0630", "benchmark": "business_letters", "date": "2026-03-16", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-opus-4-6", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1922-12-16\"],\"letter_title\":null,\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.-G.\"]}}", "model": "claude-opus-4-6", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 2788, "output_tokens": 103, "total_tokens": 2891, "input_cost_usd": 0.013940000000000001, "output_cost_usd": 0.002575, "estimated_cost_usd": 0.016515000000000002}, "duration": 4.670318841934204, "timestamp": "2026-03-16T15:50:08.769975", "parsed": {"metadata": {"send_date": ["1922-12-16"], "letter_title": null, "sender_persons": ["Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["Basler Rheinschiffahrt A.-G."], "document_number": "letter59"}}, "conversation_id": "d656b652-4017-4d6b-9a80-d15599303687", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"msg_015zg8GyA3F7LtsEnkTWwR5B\",\"content\":[{\"id\":\"toolu_012Kd6DxaRzWFLtohjhPoGuX\",\"input\":{\"metadata\":{\"send_date\":[\"1922-12-16\"],\"letter_title\":null,\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.-G.\"],\"document_number\":\"letter59\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\",\"caller\":{\"type\":\"direct\"}}],\"model\":\"claude-opus-4-6\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"inference_geo\":\"global\",\"input_tokens\":2788,\"output_tokens\":103,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.51, "f1_micro": 0.58, "cost_summary": {"total_input_tokens": 85240, "total_output_tokens": 2681, "total_tokens": 87921, "input_cost_usd": 0.42620000000000013, "output_cost_usd": 0.067025, "total_cost_usd": 0.493225}}, "normalized_score": 51.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c9f"}, "test_id": "T0641", "benchmark": "business_letters", "date": "2026-03-16", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-sonnet-4-6", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-09-09\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft Direktion\"]}}", "model": "claude-sonnet-4-6", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 2788, "output_tokens": 85, "total_tokens": 2873, "input_cost_usd": 0.008364, "output_cost_usd": 0.001275, "estimated_cost_usd": 0.009639}, "duration": 3.830749034881592, "timestamp": "2026-03-16T15:49:57.132778", "parsed": {"metadata": {"send_date": ["1932-09-09"], "letter_title": null, "sender_persons": null, "receiver_persons": ["Basler Rheinschiffahrt Aktiengesellschaft Direktion"], "document_number": "letter49"}}, "conversation_id": "384b1690-0751-49c1-96cc-87139aaefb26", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"msg_01RTXgXvm7bhzbeWxHTay78X\",\"content\":[{\"id\":\"toolu_01SJGFzZjty8wW6yHx1sw8vC\",\"input\":{\"metadata\":{\"send_date\":[\"1932-09-09\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft Direktion\"],\"document_number\":\"letter49\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\",\"caller\":{\"type\":\"direct\"}}],\"model\":\"claude-sonnet-4-6\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"inference_geo\":\"global\",\"input_tokens\":2788,\"output_tokens\":85,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.56, "f1_micro": 0.57, "cost_summary": {"total_input_tokens": 222630, "total_output_tokens": 5400, "total_tokens": 228030, "input_cost_usd": 0.6678900000000001, "output_cost_usd": 0.081, "total_cost_usd": 0.7488900000000001}}, "normalized_score": 56.00000000000001}, {"_id": {"$oid": "69d4eb12b877594bc5718c9a"}, "test_id": "T0629", "benchmark": "business_letters", "date": "2026-03-16", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-opus-4-6", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-06-28\"],\"letter_title\":null,\"sender_persons\":[\"Max Vischer\"],\"receiver_persons\":[\"P. Christ-Wackernagel\"]}}", "model": "claude-opus-4-6", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 4342, "output_tokens": 80, "total_tokens": 4422, "input_cost_usd": 0.02171, "output_cost_usd": 0.002, "estimated_cost_usd": 0.023710000000000002}, "duration": 5.739343166351318, "timestamp": "2026-03-16T15:49:46.261158", "parsed": {"metadata": {"send_date": ["1926-06-28"], "letter_title": null, "sender_persons": ["Max Vischer"], "receiver_persons": ["P. Christ-Wackernagel"], "document_number": "letter09"}}, "conversation_id": "d9cba67d-01ef-4add-b612-4b8f0d5cb268", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 1, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"msg_016V3KGw4GLydfPnP1BmhKyE\",\"content\":[{\"id\":\"toolu_019K7dswDdirGosxC3yXtaPS\",\"input\":{\"metadata\":{\"send_date\":[\"1926-06-28\"],\"letter_title\":null,\"sender_persons\":[\"Max Vischer\"],\"receiver_persons\":[\"P. Christ-Wackernagel\"],\"document_number\":\"letter09\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\",\"caller\":{\"type\":\"direct\"}}],\"model\":\"claude-opus-4-6\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"inference_geo\":\"global\",\"input_tokens\":4342,\"output_tokens\":80,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.58, "f1_micro": 0.57, "cost_summary": {"total_input_tokens": 222630, "total_output_tokens": 5656, "total_tokens": 228286, "input_cost_usd": 1.1131499999999996, "output_cost_usd": 0.14139999999999994, "total_cost_usd": 1.2545500000000003}}, "normalized_score": 57.99999999999999}, {"_id": {"$oid": "69d4eb12b877594bc5718c9c"}, "test_id": "T0684", "benchmark": "business_letters", "date": "2026-03-16", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-3.1-pro-preview", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-10-07\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":[\"Vorstandsmitglieder der Basler Personenschiffahrtsgesellschaft\"]}}", "model": "gemini-3.1-pro-preview", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 1428, "output_tokens": 83, "total_tokens": 1511, "input_cost_usd": 0.002856, "output_cost_usd": 0.000996, "estimated_cost_usd": 0.003852}, "duration": 2.94649600982666, "timestamp": "2026-03-16T19:17:30.026767", "parsed": {"metadata": {"send_date": ["1932-10-07"], "letter_title": null, "sender_persons": null, "receiver_persons": ["Vorstandsmitglieder der Basler Personenschiffahrtsgesellschaft"], "document_number": "letter53"}}, "conversation_id": "f80f8ffc-f772-49b3-97d5-a561da2b5ade", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Mon, 16 Mar 2026 18:17:36 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=2777\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"media_resolution\":null,\"code_execution_result\":null,\"executable_code\":null,\"file_data\":null,\"function_call\":null,\"function_response\":null,\"inline_data\":null,\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1932-10-07\\\"\\n ],\\n \\\"letter_title\\\": null,\\n \\\"sender_persons\\\": null,\\n \\\"receiver_persons\\\": [\\n \\\"Vorstandsmitglieder der Basler Personenschiffahrtsgesellschaft\\\"\\n ]\\n }\\n}\",\"thought\":null,\"thought_signature\":\"EjQKMgG-Pvb705u1VaY0unvlTjZ6v9nKt6RlFRoxrmUuPVvG90paLFY1i2CQSY9lwKmKgB8W\",\"video_metadata\":null}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null,\"url_context_metadata\":null}],\"create_time\":null,\"model_version\":\"gemini-3.1-pro-preview\",\"prompt_feedback\":null,\"response_id\":\"QEm4ac71M-TcnsEPuYX3oAc\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":83,\"candidates_tokens_details\":null,\"prompt_token_count\":1428,\"prompt_tokens_details\":[{\"modality\":\"IMAGE\",\"token_count\":1092},{\"modality\":\"TEXT\",\"token_count\":336}],\"thoughts_token_count\":null,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":1511,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1932-10-07\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":[\"Vorstandsmitglieder der Basler Personenschiffahrtsgesellschaft\"]}}}"}, "scoring": {"f1_macro": 0.63, "f1_micro": 0.6, "cost_summary": {"total_input_tokens": 79548, "total_output_tokens": 2440, "total_tokens": 81988, "input_cost_usd": 0.15909599999999996, "output_cost_usd": 0.029279999999999994, "total_cost_usd": 0.18837599999999996}}, "normalized_score": 63.0}, {"_id": {"$oid": "69d4eb12b877594bc5718cad"}, "test_id": "T0670", "benchmark": "business_letters", "date": "2026-03-16", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-3.1-flash-lite-preview", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1929-05-27\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"F. L\u00fctzelschwab\"]}}", "model": "gemini-3.1-flash-lite-preview", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 2520, "output_tokens": 79, "total_tokens": 2599, "input_cost_usd": 0.00063, "output_cost_usd": 0.0001185, "estimated_cost_usd": 0.0007485}, "duration": 2.035912036895752, "timestamp": "2026-03-16T19:08:08.858883", "parsed": {"metadata": {"send_date": ["1929-05-27"], "letter_title": ["null"], "sender_persons": ["Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["F. L\u00fctzelschwab"], "document_number": "letter46"}}, "conversation_id": "897b312c-6b68-40e9-a721-c1890726c9a7", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 1}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Mon, 16 Mar 2026 18:08:15 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=1710\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"media_resolution\":null,\"code_execution_result\":null,\"executable_code\":null,\"file_data\":null,\"function_call\":null,\"function_response\":null,\"inline_data\":null,\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1929-05-27\\\"],\\n \\\"letter_title\\\": [\\n \\\"null\\\"\\n ],\\n \\\"sender_persons\\\": [\\\"Basler Personenschiffahrtsgesellschaft\\\"],\\n \\\"receiver_persons\\\": [\\\"F. L\u00fctzelschwab\\\"]\\n }\\n}\",\"thought\":null,\"thought_signature\":\"EjQKMgG-Pvb7ceEspR0pyBYAEF6ZTzW_q6IOLHG43V-6NawaluD48L3J9G6JYyMGUt8mL7BE\",\"video_metadata\":null}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null,\"url_context_metadata\":null}],\"create_time\":null,\"model_version\":\"gemini-3.1-flash-lite-preview\",\"prompt_feedback\":null,\"response_id\":\"D0e4adXCKNuivdIPoJ74qA0\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":79,\"candidates_tokens_details\":null,\"prompt_token_count\":2520,\"prompt_tokens_details\":[{\"modality\":\"IMAGE\",\"token_count\":2184},{\"modality\":\"TEXT\",\"token_count\":336}],\"thoughts_token_count\":null,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":2599,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1929-05-27\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"F. L\u00fctzelschwab\"]}}}"}, "scoring": {"f1_macro": 0.56, "f1_micro": 0.57, "cost_summary": {"total_input_tokens": 126168, "total_output_tokens": 4662, "total_tokens": 130830, "input_cost_usd": 0.03154199999999998, "output_cost_usd": 0.0069929999999999975, "total_cost_usd": 0.038535}}, "normalized_score": 56.00000000000001}, {"_id": {"$oid": "69d4eb12b877594bc5718c96"}, "test_id": "T0653", "benchmark": "business_letters", "date": "2026-03-16", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5.4-2026-03-05", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-04-23\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Herrn Oettinger\"]}}", "model": "gpt-5.4-2026-03-05", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 3262, "output_tokens": 55, "total_tokens": 3317, "input_cost_usd": 0.008155, "output_cost_usd": 0.000825, "estimated_cost_usd": 0.00898}, "duration": 2.7411630153656006, "timestamp": "2026-03-16T17:05:42.006228", "parsed": {"metadata": {"send_date": ["1928-04-23"], "letter_title": ["null"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Herrn Oettinger"], "document_number": "letter27"}}, "conversation_id": "3a274b36-4f32-43c1-86b9-8bbcd48925dd", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-DK4jrxKV36Ys7DLjU6Y2aUi3in5RM\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1928-04-23\\\"],\\\"letter_title\\\":[\\\"null\\\"],\\\"sender_persons\\\":[\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"],\\\"receiver_persons\\\":[\\\"Herrn Oettinger\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-04-23\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Herrn Oettinger\"]}}}}],\"created\":1773677147,\"model\":\"gpt-5.4-2026-03-05\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":55,\"prompt_tokens\":3262,\"total_tokens\":3317,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.57, "f1_micro": 0.58, "cost_summary": {"total_input_tokens": 299668, "total_output_tokens": 3310, "total_tokens": 302978, "input_cost_usd": 0.7491700000000007, "output_cost_usd": 0.049650000000000014, "total_cost_usd": 0.7988200000000001}}, "normalized_score": 56.99999999999999}, {"_id": {"$oid": "69d4eb12b877594bc5718ca3"}, "test_id": "T0642", "benchmark": "business_letters", "date": "2026-03-16", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-sonnet-4-6", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-12-16\"],\"letter_title\":null,\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.-G.\"]}}", "model": "claude-sonnet-4-6", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 2788, "output_tokens": 93, "total_tokens": 2881, "input_cost_usd": 0.008364, "output_cost_usd": 0.001395, "estimated_cost_usd": 0.009759}, "duration": 4.084035873413086, "timestamp": "2026-03-16T15:50:07.866161", "parsed": {"metadata": {"send_date": ["1932-12-16"], "letter_title": null, "sender_persons": ["Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["Basler Rheinschiffahrt A.-G."], "document_number": "letter59"}}, "conversation_id": "73df253d-4c48-455b-851d-96745ba8cea4", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"msg_01R4upuU9RoiNXnU7GW3R8Nq\",\"content\":[{\"id\":\"toolu_01V4WLWVBB8y5NSys9yTB89u\",\"input\":{\"metadata\":{\"send_date\":[\"1932-12-16\"],\"letter_title\":null,\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.-G.\"],\"document_number\":\"letter59\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\",\"caller\":{\"type\":\"direct\"}}],\"model\":\"claude-sonnet-4-6\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"inference_geo\":\"global\",\"input_tokens\":2788,\"output_tokens\":93,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.52, "f1_micro": 0.61, "cost_summary": {"total_input_tokens": 85240, "total_output_tokens": 2370, "total_tokens": 87610, "input_cost_usd": 0.2557200000000001, "output_cost_usd": 0.035550000000000005, "total_cost_usd": 0.29127}}, "normalized_score": 52.0}, {"_id": {"$oid": "69d4eb12b877594bc5718caf"}, "test_id": "T0671", "benchmark": "business_letters", "date": "2026-03-16", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-3.1-flash-lite-preview", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-02-23\"],\"letter_title\":[\"\"],\"sender_persons\":[\"Der Pr\u00e4sident der Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrts A.-G.\"]}}", "model": "gemini-3.1-flash-lite-preview", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 1428, "output_tokens": 80, "total_tokens": 1508, "input_cost_usd": 0.000357, "output_cost_usd": 0.00012000000000000002, "estimated_cost_usd": 0.000477}, "duration": 2.2674612998962402, "timestamp": "2026-03-16T19:08:17.047820", "parsed": {"metadata": {"send_date": ["1928-02-23"], "letter_title": [""], "sender_persons": ["Der Pr\u00e4sident der Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["Basler Rheinschiffahrts A.-G."], "document_number": "letter15"}}, "conversation_id": "53a938bb-0aa9-48e7-813e-d66d0f4717b4", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Mon, 16 Mar 2026 18:08:23 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=1775\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"media_resolution\":null,\"code_execution_result\":null,\"executable_code\":null,\"file_data\":null,\"function_call\":null,\"function_response\":null,\"inline_data\":null,\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1928-02-23\\\"],\\n \\\"letter_title\\\": [\\\"\\\"],\\n \\\"sender_persons\\\": [\\\"Der Pr\u00e4sident der Basler Personenschiffahrtsgesellschaft\\\"],\\n \\\"receiver_persons\\\": [\\\"Basler Rheinschiffahrts A.-G.\\\"]\\n }\\n}\",\"thought\":null,\"thought_signature\":\"EjQKMgG-Pvb7N0_tEP3kW59R458QZ2T1HM0UiEfGKV1qmaCe3rFdnm0yFp1CiAZt2tukEjWx\",\"video_metadata\":null}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null,\"url_context_metadata\":null}],\"create_time\":null,\"model_version\":\"gemini-3.1-flash-lite-preview\",\"prompt_feedback\":null,\"response_id\":\"F0e4afvXM9SLxN8PzpOmuAo\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":80,\"candidates_tokens_details\":null,\"prompt_token_count\":1428,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":336},{\"modality\":\"IMAGE\",\"token_count\":1092}],\"thoughts_token_count\":null,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":1508,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1928-02-23\"],\"letter_title\":[\"\"],\"sender_persons\":[\"Der Pr\u00e4sident der Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrts A.-G.\"]}}}"}, "scoring": {"f1_macro": 0.53, "f1_micro": 0.62, "cost_summary": {"total_input_tokens": 46620, "total_output_tokens": 2079, "total_tokens": 48699, "input_cost_usd": 0.011654999999999999, "output_cost_usd": 0.0031185, "total_cost_usd": 0.014773499999999998}}, "normalized_score": 53.0}, {"_id": {"$oid": "69d4eb12b877594bc5718ca8"}, "test_id": "T0654", "benchmark": "business_letters", "date": "2026-03-16", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5.4-2026-03-05", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1929-05-27\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"P. L\u00fctzel Schwab\"]}}", "model": "gpt-5.4-2026-03-05", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 6036, "output_tokens": 47, "total_tokens": 6083, "cached_tokens": 4864, "input_cost_usd": 0.01509, "output_cost_usd": 0.000705, "estimated_cost_usd": 0.015795}, "duration": 3.7494537830352783, "timestamp": "2026-03-16T17:05:54.142698", "parsed": {"metadata": {"send_date": ["1929-05-27"], "letter_title": ["null"], "sender_persons": ["null"], "receiver_persons": ["P. L\u00fctzel Schwab"], "document_number": "letter46"}}, "conversation_id": "58bcba88-e240-49fc-baa7-49bee7f4d1d1", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"chatcmpl-DK4k3E0eqxjEKldEzdzVdxndGvfmD\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1929-05-27\\\"],\\\"letter_title\\\":[\\\"null\\\"],\\\"sender_persons\\\":[\\\"null\\\"],\\\"receiver_persons\\\":[\\\"P. L\u00fctzel Schwab\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1929-05-27\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"P. L\u00fctzel Schwab\"]}}}}],\"created\":1773677159,\"model\":\"gpt-5.4-2026-03-05\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":47,\"prompt_tokens\":6036,\"total_tokens\":6083,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":4864}}}"}, "scoring": {"f1_macro": 0.51, "f1_micro": 0.62, "cost_summary": {"total_input_tokens": 109290, "total_output_tokens": 1470, "total_tokens": 110760, "input_cost_usd": 0.273225, "output_cost_usd": 0.022049999999999993, "total_cost_usd": 0.295275}}, "normalized_score": 51.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c7d"}, "test_id": "T0023", "benchmark": "business_letters", "date": "2026-03-04", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "pixtral-large-2411", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\n \"metadata\": {\n \"letter_title\": [null],\n \"send_date\": [null],\n \"sender_persons\": [null],\n \"receiver_persons\": [null]\n }\n}", "model": "pixtral-large-2411", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 640, "output_tokens": 56, "total_tokens": 696, "input_cost_usd": 0.00128, "output_cost_usd": 0.000336, "estimated_cost_usd": 0.001616}, "duration": 1.1282665729522705, "timestamp": "2026-03-04T09:43:26.555664", "parsed": {"metadata": {"letter_title": [null], "send_date": [null], "sender_persons": [null], "receiver_persons": [null], "document_number": "letter11"}}, "conversation_id": "51ee49b7-f96b-47a1-b581-b7acc999814b", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"e37ab57d468340bdb1e41f1a5a793697\",\"object\":\"chat.completion\",\"model\":\"pixtral-large-2411\",\"usage\":{\"prompt_tokens\":640,\"completion_tokens\":56,\"total_tokens\":696,\"prompt_tokens_details\":{\"cached_tokens\":640}},\"created\":1772613805,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [null],\\n \\\"send_date\\\": [null],\\n \\\"sender_persons\\\": [null],\\n \\\"receiver_persons\\\": [null]\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 36480, "total_output_tokens": 3208, "total_tokens": 39688, "input_cost_usd": 0.07296000000000011, "output_cost_usd": 0.019247999999999987, "total_cost_usd": 0.0922080000000001}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718c7c"}, "test_id": "T0244", "benchmark": "business_letters", "date": "2026-03-04", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "qwen/qwen3-vl-8b-thinking", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1933-08-15\"],\"letter_title\":null,\"sender_persons\":[\"Dr. Max Heide\"],\"receiver_persons\":[\"Basler Rheinschiffahrts A.-G.\"]}}", "model": "qwen/qwen3-vl-8b-thinking", "provider": "openrouter", "finish_reason": "stop", "usage": {"input_tokens": 3111, "output_tokens": 2345, "total_tokens": 5456, "input_cost_usd": 0.000363987, "output_cost_usd": 0.003200925, "estimated_cost_usd": 0.003564912}, "duration": 18.889249801635742, "timestamp": "2026-03-04T09:02:08.602396", "parsed": {"metadata": {"send_date": ["1933-08-15"], "letter_title": null, "sender_persons": ["Dr. Max Heide"], "receiver_persons": ["Basler Rheinschiffahrts A.-G."], "document_number": "letter63"}}, "conversation_id": "9f8dc6c5-a9d3-42d1-b5a4-3bf927a73c89", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"gen-1772611310-CaK5TT5Oli87rpM6WKVN\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"receiver_persons\\\": [\\\"Basler Rheinschiffahrts A.-G.\\\"],\\n \\\"send_date\\\": [\\\"1933-08-15\\\"],\\n \\\"sender_persons\\\": [\\\"Dr. Max Heide\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1933-08-15\"],\"letter_title\":null,\"sender_persons\":[\"Dr. Max Heide\"],\"receiver_persons\":[\"Basler Rheinschiffahrts A.-G.\"]}},\"reasoning\":\"Got it, let's analyze this historical letter. First, I need to extract the required fields: letter_title, sender_persons, send_date, receiver_persons.\\n\\nStarting with send_date: The letter has \\\"Basel, den 15. Aug. 1933.\\\" So converting that to ISO format. August is 08, so 1933-08-15.\\n\\nReceiver_persons: The address line says \\\"An die Basler Rheinschiffahrts A.-G. Marktgar 5 Basel\\\". So the receiver is Basler Rheinschiffahrts A.-G. as a company. Since it's a company name, it's the receiver. So receiver_persons should be [\\\"Basler Rheinschiffahrts A.-G.\\\"].\\n\\nSender_persons: At the bottom, there's a handwritten signature: \\\"Urgen f\u00fcr Herr Dr. Max Heide\\\" \u2013 wait, looking at the signature, it's \\\"Urgen f\u00fcr Herr Dr. Max Heide\\\" but maybe it's \\\"Urgen f\u00fcr Herr Dr. Max Heide\\\" as the sender. Wait, the letter is from \\\"Basler Personenschiffahrtsgesellschaft\\\" as per the letterhead. Wait, the letterhead says \\\"BASLER PERSONENSCHIFFAHRTSGESELLSCHAFT\\\" at the top. So the sender is that company. But the signature is \\\"Urgen f\u00fcr Herr Dr. Max Heide\\\" \u2013 maybe \\\"Dr. Max Heide\\\" is the signatory. Wait, the document is a letter from the company, so the sender_persons would be the company name, but the signature is of a person. Wait, in German letters, sometimes the company's name is the sender, but the individual might be the signatory. But the task is to get the name(s) of the person(s) who wrote the letter. The handwritten signature is \\\"Urgen f\u00fcr Herr Dr. Max Heide\\\" \u2013 \\\"Urgen\\\" might be a typo or misread? Wait, the handwritten part: \\\"Urgen\\\" \u2013 maybe it's \\\"Vorstand\\\" or a name? Wait, looking at the image, the signature is \\\"Urgen f\u00fcr Herr Dr. Max Heide\\\" \u2013 perhaps \\\"Dr. Max Heide\\\" is the signatory. Let me check again.\\n\\nWait, the letterhead is \\\"BASLER PERSONENSCHIFFAHRTSGESELLSCHAFT\\\", and at the bottom, there's a handwritten note: \\\"Urgen f\u00fcr Herr Dr. Max Heide\\\". But in German letters, \\\"Urgen\\\" might be a misreading. Wait, maybe it's \\\"Vorstand\\\" (board of directors) but \\\"Urgen\\\" doesn't fit. Alternatively, perhaps it's \\\"Urgen\\\" as a typo for \\\"Vorstand\\\"? No. Wait, maybe the signature is \\\"F\u00fcr den Vorstand: Dr. Max Heide\\\" \u2013 but the image shows \\\"Urgen f\u00fcr Herr Dr. Max Heide\\\". Wait, maybe \\\"Urgen\\\" is a misspelling. Alternatively, maybe the signature is from Dr. Max Heide, so sender_persons would be [\\\"Dr. Max Heide\\\"].\\n\\nLetter title: The example shows it's a title. But the letter is a formal business letter. There's no explicit title like \\\"Petition...\\\", but the content is about sending complaints (Beschwerden). The title might be a placeholder, but maybe the letter title isn't explicitly stated. Wait, the task says if not included, set to null. So letter_title: does the letter have a title? The letter itself doesn't have a title line, so perhaps it's null.\\n\\nWait, the example says if not included, set to null. So letter_title is not present here, so null.\\n\\nLet's confirm each field:\\n\\n- letter_title: No title given, so null.\\n- sender_persons: The handwritten signature indicates \\\"Dr. Max Heide\\\" as the signatory. So sender_persons = [\\\"Dr. Max Heide\\\"].\\n- send_date: \\\"den 15. Aug. 1933\\\" \u2192 1933-08-15.\\n- receiver_persons: \\\"An die Basler Rheinschiffahrts A.-G. Marktgar 5 Basel\\\" \u2192 receiver is Basler Rheinschiffahrts A.-G., so [\\\"Basler Rheinschiffahrts A.-G.\\\"].\\n\\nWait, but the letterhead is \\\"BASLER PERSONENSCHIFFAHRTSGESELLSCHAFT\\\", which is the sender company. But the question is about the sender_persons (the person(s) who wrote the letter). So if the company is the sender, but the person is Dr. Max Heide, then sender_persons would be [\\\"Dr. Max Heide\\\"].\\n\\nLet me check the German convention: in business letters, the company sends it, but the individual (director) signs. So the sender_persons would be the person who signed, which is Dr. Max Heide.\\n\\nYes, so sender_persons: [\\\"Dr. Max Heide\\\"]\\n\\nReceiver_persons: [\\\"Basler Rheinschiffahrts A.-G.\\\"]\\n\\nSend_date: 1933-08-15\\n\\nLetter_title: not present, so null.\\n\\nWait, but the example in the problem statement says that letter_title is a list, even if single. But if there's no title, it's null.\\n\\nSo putting it all together:\\n\\n{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"receiver_persons\\\": [\\\"Basler Rheinschiffahrts A.-G.\\\"],\\n \\\"send_date\\\": [\\\"1933-08-15\\\"],\\n \\\"sender_persons\\\": [\\\"Dr. Max Heide\\\"]\\n }\\n}\\n\\nWait, but let's check the exact text in the image. The image shows the letter has:\\n\\n- At the top: \\\"BASLER PERSONENSCHIFFAHRTSGESELLSCHAFT\\\" (letterhead)\\n- Date: \\\"Basel, den 15. Aug. 1933.\\\"\\n- \\\"An die Basler Rheinschiffahrts A.-G. Marktgar 5 Basel\\\"\\n- Content: \\\"Sehr geehrte Herren, ... Mit vorz\u00fcglicher Hochachtung Basler Personenschiffahrtsgeellschaft Der Gesch\u00e4ftsf\u00fchrer\\\"\\n- Signature: \\\"Urgen f\u00fcr Herr Dr. Max Heide\\\"\\n\\nWait, the signature is \\\"Urgen f\u00fcr Herr Dr. Max Heide\\\". Maybe \\\"Urgen\\\" is a typo or misreading of \\\"Vorstand\\\" (board)? But in German, sometimes signatures are \\\"F\u00fcr den Vorstand: ...\\\" but here it's \\\"Urgen f\u00fcr Herr Dr. Max Heide\\\". Alternatively, maybe \\\"Urgen\\\" is the name of the person, but that's unlikely. Wait, perhaps \\\"Urgen\\\" is a misspelling of \\\"Vorstand\\\" (which is \\\"board of directors\\\"), but the text is \\\"Urgen\\\", which is not a standard term.\\n\\nAlternatively, maybe the signature is \\\"Vorstand f\u00fcr Herr Dr. Max Heide\\\" but written as \\\"Urgen\\\". Wait, \\\"Urgen\\\" might be a typo for \\\"Vorstand\\\" \u2013 no, Vorstand is with a 'V' and 'o'. Maybe it's a misprint. Alternatively, perhaps \\\"Urgen\\\" is the surname. But \\\"Urgen\\\" as a name is rare. Let's see: Dr. Max Heide is the name, so the sender_persons would be \\\"Dr. Max Heide\\\".\\n\\nWait, in the letter, the closing is \\\"Mit vorz\u00fcglicher Hochachtung\\\" followed by \\\"Basler Personenschiffahrtsgeellschaft Der Gesch\u00e4ftsf\u00fchrer\\\", so the company is the sender, and the Gesch\u00e4ftsf\u00fchrer (manager) signed it. So the sender_persons would be the Gesch\u00e4ftsf\u00fchrer, which is Dr. Max Heide.\\n\\nYes, so sender_persons is [\\\"Dr. Max Heide\\\"]\\n\\nReceiver_persons: \\\"Basler Rheinschiffahrts A.-G.\\\" as the company receiving.\\n\\nLetter_title: Not present, so null.\\n\\nSend_date: 1933-08-15.\\n\\nSo the JSON should be:\\n\\n{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"receiver_persons\\\": [\\\"Basler Rheinschiffahrts A.-G.\\\"],\\n \\\"send_date\\\": [\\\"1933-08-15\\\"],\\n \\\"sender_persons\\\": [\\\"Dr. Max Heide\\\"]\\n }\\n}\\n\\nWait, but in the problem statement's example, the values are arrays, even if single. So the nulls should be as per the schema.\\n\\nWait, the schema says:\\n\\n\\\"additionalProperties\\\": false,\\n\\\"properties\\\": {\\n \\\"metadata\\\": {\\n \\\"$ref\\\": \\\"#/$defs/Metadata\\\"\\n }\\n},\\n\\\"required\\\": [\\\"metadata\\\"],\\n\\\"title\\\": \\\"Document\\\",\\n\\\"type\\\": \\\"object\\\"\\n\\nAnd in the Metadata:\\n\\n\\\"required\\\": [\\\"send_date\\\", \\\"letter_title\\\", \\\"sender_persons\\\", \\\"receiver_persons\\\"],\\n\\\"anyOf\\\": [{\\\"items\\\": {\\\"type\\\": \\\"string\\\"}, \\\"type\\\": \\\"array\\\"}, {\\\"type\\\": \\\"null\\\"}] for each.\\n\\nSo for each key, it's either a list of strings or null.\\n\\nSo for letter_title, if it's not present, it's null. But the schema says \\\"anyOf\\\" for the value of each property (letter_title, etc.) is either an array of strings or null.\\n\\nSo for example, in the example:\\n\\n\\\"letter_title\\\": [\\\"Petition for Environmental Protection\\\"], which is an array of one string.\\n\\nIf no title, it's null.\\n\\nSo in this case, letter_title is not present, so set to null.\\n\\nReceiver_persons: the company name, so a list with one string.\\n\\nSame for others.\\n\\nSo the final JSON should have:\\n\\n\\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"receiver_persons\\\": [\\\"Basler Rheinschiffahrts A.-G.\\\"],\\n \\\"send_date\\\": [\\\"1933-08-15\\\"],\\n \\\"sender_persons\\\": [\\\"Dr. Max Heide\\\"]\\n}\\n\\nWait, but let's check the exact date: \\\"den 15. Aug. 1933\\\" \u2192 August 15, 1933 \u2192 ISO is 1933-08-15.\\n\\nYes.\\n\\nAnd the receiver: \\\"An die Basler Rheinschiffahrts A.-G. Marktgar 5 Basel\\\" \u2192 so the receiver is Basler Rheinschiffahrts A.-G. (the company).\\n\\nSender: the signature is for Dr. Max Heide.\\n\\nYes.\\n\\nSo the JSON should be as above.\\n\",\"reasoning_details\":[{\"type\":\"reasoning.text\",\"text\":\"Got it, let's analyze this historical letter. First, I need to extract the required fields: letter_title, sender_persons, send_date, receiver_persons.\\n\\nStarting with send_date: The letter has \\\"Basel, den 15. Aug. 1933.\\\" So converting that to ISO format. August is 08, so 1933-08-15.\\n\\nReceiver_persons: The address line says \\\"An die Basler Rheinschiffahrts A.-G. Marktgar 5 Basel\\\". So the receiver is Basler Rheinschiffahrts A.-G. as a company. Since it's a company name, it's the receiver. So receiver_persons should be [\\\"Basler Rheinschiffahrts A.-G.\\\"].\\n\\nSender_persons: At the bottom, there's a handwritten signature: \\\"Urgen f\u00fcr Herr Dr. Max Heide\\\" \u2013 wait, looking at the signature, it's \\\"Urgen f\u00fcr Herr Dr. Max Heide\\\" but maybe it's \\\"Urgen f\u00fcr Herr Dr. Max Heide\\\" as the sender. Wait, the letter is from \\\"Basler Personenschiffahrtsgesellschaft\\\" as per the letterhead. Wait, the letterhead says \\\"BASLER PERSONENSCHIFFAHRTSGESELLSCHAFT\\\" at the top. So the sender is that company. But the signature is \\\"Urgen f\u00fcr Herr Dr. Max Heide\\\" \u2013 maybe \\\"Dr. Max Heide\\\" is the signatory. Wait, the document is a letter from the company, so the sender_persons would be the company name, but the signature is of a person. Wait, in German letters, sometimes the company's name is the sender, but the individual might be the signatory. But the task is to get the name(s) of the person(s) who wrote the letter. The handwritten signature is \\\"Urgen f\u00fcr Herr Dr. Max Heide\\\" \u2013 \\\"Urgen\\\" might be a typo or misread? Wait, the handwritten part: \\\"Urgen\\\" \u2013 maybe it's \\\"Vorstand\\\" or a name? Wait, looking at the image, the signature is \\\"Urgen f\u00fcr Herr Dr. Max Heide\\\" \u2013 perhaps \\\"Dr. Max Heide\\\" is the signatory. Let me check again.\\n\\nWait, the letterhead is \\\"BASLER PERSONENSCHIFFAHRTSGESELLSCHAFT\\\", and at the bottom, there's a handwritten note: \\\"Urgen f\u00fcr Herr Dr. Max Heide\\\". But in German letters, \\\"Urgen\\\" might be a misreading. Wait, maybe it's \\\"Vorstand\\\" (board of directors) but \\\"Urgen\\\" doesn't fit. Alternatively, perhaps it's \\\"Urgen\\\" as a typo for \\\"Vorstand\\\"? No. Wait, maybe the signature is \\\"F\u00fcr den Vorstand: Dr. Max Heide\\\" \u2013 but the image shows \\\"Urgen f\u00fcr Herr Dr. Max Heide\\\". Wait, maybe \\\"Urgen\\\" is a misspelling. Alternatively, maybe the signature is from Dr. Max Heide, so sender_persons would be [\\\"Dr. Max Heide\\\"].\\n\\nLetter title: The example shows it's a title. But the letter is a formal business letter. There's no explicit title like \\\"Petition...\\\", but the content is about sending complaints (Beschwerden). The title might be a placeholder, but maybe the letter title isn't explicitly stated. Wait, the task says if not included, set to null. So letter_title: does the letter have a title? The letter itself doesn't have a title line, so perhaps it's null.\\n\\nWait, the example says if not included, set to null. So letter_title is not present here, so null.\\n\\nLet's confirm each field:\\n\\n- letter_title: No title given, so null.\\n- sender_persons: The handwritten signature indicates \\\"Dr. Max Heide\\\" as the signatory. So sender_persons = [\\\"Dr. Max Heide\\\"].\\n- send_date: \\\"den 15. Aug. 1933\\\" \u2192 1933-08-15.\\n- receiver_persons: \\\"An die Basler Rheinschiffahrts A.-G. Marktgar 5 Basel\\\" \u2192 receiver is Basler Rheinschiffahrts A.-G., so [\\\"Basler Rheinschiffahrts A.-G.\\\"].\\n\\nWait, but the letterhead is \\\"BASLER PERSONENSCHIFFAHRTSGESELLSCHAFT\\\", which is the sender company. But the question is about the sender_persons (the person(s) who wrote the letter). So if the company is the sender, but the person is Dr. Max Heide, then sender_persons would be [\\\"Dr. Max Heide\\\"].\\n\\nLet me check the German convention: in business letters, the company sends it, but the individual (director) signs. So the sender_persons would be the person who signed, which is Dr. Max Heide.\\n\\nYes, so sender_persons: [\\\"Dr. Max Heide\\\"]\\n\\nReceiver_persons: [\\\"Basler Rheinschiffahrts A.-G.\\\"]\\n\\nSend_date: 1933-08-15\\n\\nLetter_title: not present, so null.\\n\\nWait, but the example in the problem statement says that letter_title is a list, even if single. But if there's no title, it's null.\\n\\nSo putting it all together:\\n\\n{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"receiver_persons\\\": [\\\"Basler Rheinschiffahrts A.-G.\\\"],\\n \\\"send_date\\\": [\\\"1933-08-15\\\"],\\n \\\"sender_persons\\\": [\\\"Dr. Max Heide\\\"]\\n }\\n}\\n\\nWait, but let's check the exact text in the image. The image shows the letter has:\\n\\n- At the top: \\\"BASLER PERSONENSCHIFFAHRTSGESELLSCHAFT\\\" (letterhead)\\n- Date: \\\"Basel, den 15. Aug. 1933.\\\"\\n- \\\"An die Basler Rheinschiffahrts A.-G. Marktgar 5 Basel\\\"\\n- Content: \\\"Sehr geehrte Herren, ... Mit vorz\u00fcglicher Hochachtung Basler Personenschiffahrtsgeellschaft Der Gesch\u00e4ftsf\u00fchrer\\\"\\n- Signature: \\\"Urgen f\u00fcr Herr Dr. Max Heide\\\"\\n\\nWait, the signature is \\\"Urgen f\u00fcr Herr Dr. Max Heide\\\". Maybe \\\"Urgen\\\" is a typo or misreading of \\\"Vorstand\\\" (board)? But in German, sometimes signatures are \\\"F\u00fcr den Vorstand: ...\\\" but here it's \\\"Urgen f\u00fcr Herr Dr. Max Heide\\\". Alternatively, maybe \\\"Urgen\\\" is the name of the person, but that's unlikely. Wait, perhaps \\\"Urgen\\\" is a misspelling of \\\"Vorstand\\\" (which is \\\"board of directors\\\"), but the text is \\\"Urgen\\\", which is not a standard term.\\n\\nAlternatively, maybe the signature is \\\"Vorstand f\u00fcr Herr Dr. Max Heide\\\" but written as \\\"Urgen\\\". Wait, \\\"Urgen\\\" might be a typo for \\\"Vorstand\\\" \u2013 no, Vorstand is with a 'V' and 'o'. Maybe it's a misprint. Alternatively, perhaps \\\"Urgen\\\" is the surname. But \\\"Urgen\\\" as a name is rare. Let's see: Dr. Max Heide is the name, so the sender_persons would be \\\"Dr. Max Heide\\\".\\n\\nWait, in the letter, the closing is \\\"Mit vorz\u00fcglicher Hochachtung\\\" followed by \\\"Basler Personenschiffahrtsgeellschaft Der Gesch\u00e4ftsf\u00fchrer\\\", so the company is the sender, and the Gesch\u00e4ftsf\u00fchrer (manager) signed it. So the sender_persons would be the Gesch\u00e4ftsf\u00fchrer, which is Dr. Max Heide.\\n\\nYes, so sender_persons is [\\\"Dr. Max Heide\\\"]\\n\\nReceiver_persons: \\\"Basler Rheinschiffahrts A.-G.\\\" as the company receiving.\\n\\nLetter_title: Not present, so null.\\n\\nSend_date: 1933-08-15.\\n\\nSo the JSON should be:\\n\\n{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"receiver_persons\\\": [\\\"Basler Rheinschiffahrts A.-G.\\\"],\\n \\\"send_date\\\": [\\\"1933-08-15\\\"],\\n \\\"sender_persons\\\": [\\\"Dr. Max Heide\\\"]\\n }\\n}\\n\\nWait, but in the problem statement's example, the values are arrays, even if single. So the nulls should be as per the schema.\\n\\nWait, the schema says:\\n\\n\\\"additionalProperties\\\": false,\\n\\\"properties\\\": {\\n \\\"metadata\\\": {\\n \\\"$ref\\\": \\\"#/$defs/Metadata\\\"\\n }\\n},\\n\\\"required\\\": [\\\"metadata\\\"],\\n\\\"title\\\": \\\"Document\\\",\\n\\\"type\\\": \\\"object\\\"\\n\\nAnd in the Metadata:\\n\\n\\\"required\\\": [\\\"send_date\\\", \\\"letter_title\\\", \\\"sender_persons\\\", \\\"receiver_persons\\\"],\\n\\\"anyOf\\\": [{\\\"items\\\": {\\\"type\\\": \\\"string\\\"}, \\\"type\\\": \\\"array\\\"}, {\\\"type\\\": \\\"null\\\"}] for each.\\n\\nSo for each key, it's either a list of strings or null.\\n\\nSo for letter_title, if it's not present, it's null. But the schema says \\\"anyOf\\\" for the value of each property (letter_title, etc.) is either an array of strings or null.\\n\\nSo for example, in the example:\\n\\n\\\"letter_title\\\": [\\\"Petition for Environmental Protection\\\"], which is an array of one string.\\n\\nIf no title, it's null.\\n\\nSo in this case, letter_title is not present, so set to null.\\n\\nReceiver_persons: the company name, so a list with one string.\\n\\nSame for others.\\n\\nSo the final JSON should have:\\n\\n\\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"receiver_persons\\\": [\\\"Basler Rheinschiffahrts A.-G.\\\"],\\n \\\"send_date\\\": [\\\"1933-08-15\\\"],\\n \\\"sender_persons\\\": [\\\"Dr. Max Heide\\\"]\\n}\\n\\nWait, but let's check the exact date: \\\"den 15. Aug. 1933\\\" \u2192 August 15, 1933 \u2192 ISO is 1933-08-15.\\n\\nYes.\\n\\nAnd the receiver: \\\"An die Basler Rheinschiffahrts A.-G. Marktgar 5 Basel\\\" \u2192 so the receiver is Basler Rheinschiffahrts A.-G. (the company).\\n\\nSender: the signature is for Dr. Max Heide.\\n\\nYes.\\n\\nSo the JSON should be as above.\\n\",\"format\":\"unknown\",\"index\":0}]},\"native_finish_reason\":\"stop\"}],\"created\":1772611310,\"model\":\"qwen/qwen3-vl-8b-thinking\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":2345,\"prompt_tokens\":3111,\"total_tokens\":5456,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":0,\"reasoning_tokens\":2277,\"rejected_prediction_tokens\":null,\"image_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0,\"cache_write_tokens\":0,\"video_tokens\":0},\"cost\":0.003564912,\"is_byok\":false,\"cost_details\":{\"upstream_inference_cost\":0.00548448,\"upstream_inference_prompt_cost\":0.00055998,\"upstream_inference_completions_cost\":0.0049245}},\"provider\":\"Alibaba\"}"}, "scoring": {"f1_macro": 0.54, "f1_micro": 0.63, "cost_summary": {"total_input_tokens": 102995, "total_output_tokens": 79559, "total_tokens": 182554, "input_cost_usd": 0.012050414999999997, "output_cost_usd": 0.108598035, "total_cost_usd": 0.12064845000000002}}, "normalized_score": 54.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c7b"}, "test_id": "T0245", "benchmark": "business_letters", "date": "2026-03-04", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "qwen/qwen3-vl-8b-thinking", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-04-26\"],\"letter_title\":null,\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Max Oettinger\"]}}", "model": "qwen/qwen3-vl-8b-thinking", "provider": "openrouter", "finish_reason": "stop", "usage": {"input_tokens": 3111, "output_tokens": 1219, "total_tokens": 4330, "input_cost_usd": 0.000363987, "output_cost_usd": 0.001663935, "estimated_cost_usd": 0.002027922}, "duration": 10.215837717056274, "timestamp": "2026-03-04T09:40:18.298103", "parsed": {"metadata": {"send_date": ["1928-04-26"], "letter_title": null, "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Max Oettinger"], "document_number": "letter29"}}, "conversation_id": "99d31577-96ad-46fa-90ba-aae049b92d5f", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"gen-1772613608-EOXLkYswqlpuUMafiLos\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"receiver_persons\\\": [\\\"Max Oettinger\\\"],\\n \\\"send_date\\\": [\\\"1928-04-26\\\"],\\n \\\"sender_persons\\\": [\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-04-26\"],\"letter_title\":null,\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Max Oettinger\"]}},\"reasoning\":\"So, let's analyze the letter step by step.\\n\\nFirst, the letter title. The letter is a business correspondence. The content mentions confirming receipt of previous documents, so it's likely an acknowledgment. But the letter itself doesn't have a specific title like \\\"Petition...\\\" in the example. Wait, in business letters, sometimes the title is implied by the context. However, the example shows a title as a string. Looking at the letter, there's no explicit title. Wait, the instruction says: if not included, set to null. But let's check. The letter's main purpose is confirming receipt of written documents. So maybe the title would be something like \\\"Confirmation of Receipt of Documents\\\" or similar. Wait, but the example in the problem statement shows a title as a string. Wait, the problem says: \\\"extract the values of the following keys from the letter\\\". So the letter_title is the title of the letter. In business letters, the title might be absent, but let's see. Wait, the letter is from Basler Rheinschiffahrt-Aktiengesellschaft to Herrn Max Oettinger. The content is confirming receipt of their letter dated 25th (ds. probably denotes \\\"des\\\" in German, meaning day of the month). The text says \\\"Wir best\u00e4tigen den Empfang Ihres Schreibens vom 25. ds. mit den darin unter 1\u20135 erw\u00e4hnten Schriftst\u00fccken.\\\" So it's an acknowledgment of receipt. So the title might be \\\"Confirmation of Receipt\\\". But does the letter have a specific title? Looking at the document, there's no title header. So perhaps it's null? Wait, the instruction says: \\\"if a piece of information is not included in the letter, set the value for the corresponding key to 'null'\\\". So if the letter doesn't have a title, then it's null. Wait, but maybe the title is implied by the context. Wait, the example shows a title as [\\\"Petition for Environmental Protection\\\"], but that's an example. In reality, the letter may not have a title. Let's check the document: the top left has the sender's company name, then the date on the right. The text is the body. So the letter_title might be null.\\n\\nNext, sender_persons. The sender is the company: Basler Rheinschiffahrt-Aktiengesellschaft. Also, the signatures at the bottom: \\\"Hochachtend\\\" followed by \\\"BASLER RHEINSCHIFFFAHRT-AKTIEGESellschaft\\\" (with signatures). So the sender is the company, so the sender_persons would be [\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"].\\n\\nSend_date: The date is \\\"Basel, den 26. April 1928.\\\" So in ISO format: 1928-04-26.\\n\\nReceiver_persons: The recipient is \\\"Herrn Max Oettinger, Verkehrsbureau, Basel.\\\" So the name is Max Oettinger, so receiver_persons is [\\\"Max Oettinger\\\"].\\n\\nWait, let's confirm each part:\\n\\n- sender_persons: The company is the sender, so the company name is the sender. In business letters, the sender is the organization. So the sender_persons is [\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"].\\n\\n- receiver_persons: The recipient is listed as \\\"Herrn Max Oettinger, Verkehrsbureau, Basel.\\\" So the person is Max Oettinger. So receiver_persons is [\\\"Max Oettinger\\\"].\\n\\n- send_date: \\\"26. April 1928\\\" is April 26, 1928. In ISO format, YYYY-MM-DD is 1928-04-26.\\n\\n- letter_title: Is there a title? The letter starts with the sender's info, then the date, then the body. The body is a confirmation. There's no explicit title line. So letter_title should be null.\\n\\nWait, the problem statement says: \\\"if a piece of information is not included in the letter, set the value for the corresponding key to 'null'\\\".\\n\\nSo:\\n\\nletter_title: null (since there's no title specified in the letter)\\n\\nsender_persons: [\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"]\\n\\nsend_date: [\\\"1928-04-26\\\"]\\n\\nreceiver_persons: [\\\"Max Oettinger\\\"]\\n\\nWait, but in the receiver_persons, the text says \\\"Herrn Max Oettinger\\\", so the name is Max Oettinger. The \\\"Herrn\\\" is the title, but the name is Max Oettinger. So receiver_persons is [\\\"Max Oettinger\\\"].\\n\\nNow, check if any of these are missing.\\n\\nLet's verify:\\n\\nSender: The company is Basler Rheinschiffahrt-Aktiengesellschaft. The letter is from them, as the body is signed by them and the header is their company details.\\n\\nReceiver: Herrn Max Oettinger, Verkehrsbureau, Basel. So the person is Max Oettinger.\\n\\nDate: 26. April 1928 \u2192 1928-04-26.\\n\\nLetter title: The document doesn't have a title line, so it's null.\\n\\nYes, that's correct.\\n\\nSo putting it all together in the required JSON structure.\\n\",\"reasoning_details\":[{\"type\":\"reasoning.text\",\"text\":\"So, let's analyze the letter step by step.\\n\\nFirst, the letter title. The letter is a business correspondence. The content mentions confirming receipt of previous documents, so it's likely an acknowledgment. But the letter itself doesn't have a specific title like \\\"Petition...\\\" in the example. Wait, in business letters, sometimes the title is implied by the context. However, the example shows a title as a string. Looking at the letter, there's no explicit title. Wait, the instruction says: if not included, set to null. But let's check. The letter's main purpose is confirming receipt of written documents. So maybe the title would be something like \\\"Confirmation of Receipt of Documents\\\" or similar. Wait, but the example in the problem statement shows a title as a string. Wait, the problem says: \\\"extract the values of the following keys from the letter\\\". So the letter_title is the title of the letter. In business letters, the title might be absent, but let's see. Wait, the letter is from Basler Rheinschiffahrt-Aktiengesellschaft to Herrn Max Oettinger. The content is confirming receipt of their letter dated 25th (ds. probably denotes \\\"des\\\" in German, meaning day of the month). The text says \\\"Wir best\u00e4tigen den Empfang Ihres Schreibens vom 25. ds. mit den darin unter 1\u20135 erw\u00e4hnten Schriftst\u00fccken.\\\" So it's an acknowledgment of receipt. So the title might be \\\"Confirmation of Receipt\\\". But does the letter have a specific title? Looking at the document, there's no title header. So perhaps it's null? Wait, the instruction says: \\\"if a piece of information is not included in the letter, set the value for the corresponding key to 'null'\\\". So if the letter doesn't have a title, then it's null. Wait, but maybe the title is implied by the context. Wait, the example shows a title as [\\\"Petition for Environmental Protection\\\"], but that's an example. In reality, the letter may not have a title. Let's check the document: the top left has the sender's company name, then the date on the right. The text is the body. So the letter_title might be null.\\n\\nNext, sender_persons. The sender is the company: Basler Rheinschiffahrt-Aktiengesellschaft. Also, the signatures at the bottom: \\\"Hochachtend\\\" followed by \\\"BASLER RHEINSCHIFFFAHRT-AKTIEGESellschaft\\\" (with signatures). So the sender is the company, so the sender_persons would be [\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"].\\n\\nSend_date: The date is \\\"Basel, den 26. April 1928.\\\" So in ISO format: 1928-04-26.\\n\\nReceiver_persons: The recipient is \\\"Herrn Max Oettinger, Verkehrsbureau, Basel.\\\" So the name is Max Oettinger, so receiver_persons is [\\\"Max Oettinger\\\"].\\n\\nWait, let's confirm each part:\\n\\n- sender_persons: The company is the sender, so the company name is the sender. In business letters, the sender is the organization. So the sender_persons is [\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"].\\n\\n- receiver_persons: The recipient is listed as \\\"Herrn Max Oettinger, Verkehrsbureau, Basel.\\\" So the person is Max Oettinger. So receiver_persons is [\\\"Max Oettinger\\\"].\\n\\n- send_date: \\\"26. April 1928\\\" is April 26, 1928. In ISO format, YYYY-MM-DD is 1928-04-26.\\n\\n- letter_title: Is there a title? The letter starts with the sender's info, then the date, then the body. The body is a confirmation. There's no explicit title line. So letter_title should be null.\\n\\nWait, the problem statement says: \\\"if a piece of information is not included in the letter, set the value for the corresponding key to 'null'\\\".\\n\\nSo:\\n\\nletter_title: null (since there's no title specified in the letter)\\n\\nsender_persons: [\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"]\\n\\nsend_date: [\\\"1928-04-26\\\"]\\n\\nreceiver_persons: [\\\"Max Oettinger\\\"]\\n\\nWait, but in the receiver_persons, the text says \\\"Herrn Max Oettinger\\\", so the name is Max Oettinger. The \\\"Herrn\\\" is the title, but the name is Max Oettinger. So receiver_persons is [\\\"Max Oettinger\\\"].\\n\\nNow, check if any of these are missing.\\n\\nLet's verify:\\n\\nSender: The company is Basler Rheinschiffahrt-Aktiengesellschaft. The letter is from them, as the body is signed by them and the header is their company details.\\n\\nReceiver: Herrn Max Oettinger, Verkehrsbureau, Basel. So the person is Max Oettinger.\\n\\nDate: 26. April 1928 \u2192 1928-04-26.\\n\\nLetter title: The document doesn't have a title line, so it's null.\\n\\nYes, that's correct.\\n\\nSo putting it all together in the required JSON structure.\\n\",\"format\":\"unknown\",\"index\":0}]},\"native_finish_reason\":\"stop\"}],\"created\":1772613608,\"model\":\"qwen/qwen3-vl-8b-thinking\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":1219,\"prompt_tokens\":3111,\"total_tokens\":4330,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":0,\"reasoning_tokens\":1150,\"rejected_prediction_tokens\":null,\"image_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0,\"cache_write_tokens\":0,\"video_tokens\":0},\"cost\":0.002027922,\"is_byok\":false,\"cost_details\":{\"upstream_inference_cost\":0.00311988,\"upstream_inference_prompt_cost\":0.00055998,\"upstream_inference_completions_cost\":0.0025599}},\"provider\":\"Alibaba\"}"}, "scoring": {"f1_macro": 0.52, "f1_micro": 0.47, "cost_summary": {"total_input_tokens": 177734, "total_output_tokens": 84177, "total_tokens": 261911, "input_cost_usd": 0.020794878, "output_cost_usd": 0.114901605, "total_cost_usd": 0.135696483}}, "normalized_score": 52.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c78"}, "test_id": "T0535", "benchmark": "business_letters", "date": "2026-02-18", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-large-2512", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":null,\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":null}}", "model": "mistral-large-2512", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 42, "total_tokens": 627, "input_cost_usd": 0.0002925, "output_cost_usd": 6.3e-05, "estimated_cost_usd": 0.0003555}, "duration": 1.4393939971923828, "timestamp": "2026-02-18T11:46:04.483436", "parsed": {"metadata": {"letter_title": null, "send_date": null, "sender_persons": null, "receiver_persons": null, "document_number": "letter01"}}, "conversation_id": "dc4bf1a9-c304-43e8-9aa3-8a5a06691abc", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"a97a4243f2f04710b40e37864a2224a7\",\"object\":\"chat.completion\",\"model\":\"mistral-large-2512\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":42,\"total_tokens\":627,\"prompt_tokens_details\":{\"cached_tokens\":16}},\"created\":1771411563,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"send_date\\\": null,\\n \\\"sender_persons\\\": null,\\n \\\"receiver_persons\\\": null\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 18720, "total_output_tokens": 1376, "total_tokens": 20096, "input_cost_usd": 0.00936, "output_cost_usd": 0.002063999999999999, "total_cost_usd": 0.011424}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718c6d"}, "test_id": "T0188", "benchmark": "business_letters", "date": "2026-02-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-large-2411", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":null,\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":null}}", "model": "mistral-large-2411", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 640, "output_tokens": 51, "total_tokens": 691, "input_cost_usd": 0.00128, "output_cost_usd": 0.000306, "estimated_cost_usd": 0.0015860000000000002}, "duration": 1.5471901893615723, "timestamp": "2026-02-17T14:42:55.212936", "parsed": {"metadata": {"letter_title": null, "send_date": null, "sender_persons": null, "receiver_persons": null, "document_number": "letter27"}}, "conversation_id": "79d64a31-6a57-478d-bec7-a0ecad341c56", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"744773e5c40a4ccf99b5c7a182f21cfe\",\"object\":\"chat.completion\",\"model\":\"mistral-large-2411\",\"usage\":{\"prompt_tokens\":640,\"completion_tokens\":51,\"total_tokens\":691,\"prompt_tokens_details\":{\"cached_tokens\":640}},\"created\":1771335773,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"send_date\\\": null,\\n \\\"sender_persons\\\": null,\\n \\\"receiver_persons\\\": null\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 36480, "total_output_tokens": 2774, "total_tokens": 39254, "input_cost_usd": 0.07296000000000011, "output_cost_usd": 0.016644000000000013, "total_cost_usd": 0.08960400000000003}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718c73"}, "test_id": "T0113", "benchmark": "business_letters", "date": "2026-02-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-11-24\"],\"letter_title\":null,\"sender_persons\":[\"Dr. Max Vischer\",\"Dr. P. C. von Planta\"],\"receiver_persons\":[\"Herrn A. Oettinger\"]}}", "model": "gpt-5-mini-2025-08-07", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 2256, "output_tokens": 895, "total_tokens": 3151, "input_cost_usd": 0.000564, "output_cost_usd": 0.00179, "estimated_cost_usd": 0.002354}, "duration": 8.765267133712769, "timestamp": "2026-02-17T11:55:46.057675", "parsed": {"metadata": {"send_date": ["1932-11-24"], "letter_title": null, "sender_persons": ["Dr. Max Vischer", "Dr. P. C. von Planta"], "receiver_persons": ["Herrn A. Oettinger"], "document_number": "letter58"}}, "conversation_id": "426090cd-fbbc-4c36-aee0-a7704e351c4c", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 1, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-DAD1ugFANNhb9jDMPRAHM1gqgboXx\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1932-11-24\\\"],\\\"letter_title\\\":null,\\\"sender_persons\\\":[\\\"Dr. Max Vischer\\\",\\\"Dr. P. C. von Planta\\\"],\\\"receiver_persons\\\":[\\\"Herrn A. Oettinger\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1932-11-24\"],\"letter_title\":null,\"sender_persons\":[\"Dr. Max Vischer\",\"Dr. P. C. von Planta\"],\"receiver_persons\":[\"Herrn A. Oettinger\"]}}}}],\"created\":1771325738,\"model\":\"gpt-5-mini-2025-08-07\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":895,\"prompt_tokens\":2256,\"total_tokens\":3151,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":832,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.59, "f1_micro": 0.53, "cost_summary": {"total_input_tokens": 127000, "total_output_tokens": 32526, "total_tokens": 159526, "input_cost_usd": 0.03174999999999999, "output_cost_usd": 0.065052, "total_cost_usd": 0.09680199999999999}}, "normalized_score": 59.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c69"}, "test_id": "T0243", "benchmark": "business_letters", "date": "2026-02-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "qwen/qwen3-vl-8b-thinking", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-10-15\"],\"letter_title\":[\"Betrifft Darlehen f\u00fcr den Bau des neuen Personenschiffes.\"],\"sender_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft Basel\"],\"receiver_persons\":[\"Herrn Dr. Max Vischer\"]}}", "model": "qwen/qwen3-vl-8b-thinking", "provider": "openrouter", "finish_reason": "stop", "usage": {"input_tokens": 5633, "output_tokens": 1916, "total_tokens": 7549, "input_cost_usd": 0.00101394, "output_cost_usd": 0.0040236000000000004, "estimated_cost_usd": 0.00503754}, "duration": 17.305020332336426, "timestamp": "2026-02-17T15:23:14.865926", "parsed": {"metadata": {"send_date": ["1932-10-15"], "letter_title": ["Betrifft Darlehen f\u00fcr den Bau des neuen Personenschiffes."], "sender_persons": ["Basler Rheinschiffahrt Aktiengesellschaft Basel"], "receiver_persons": ["Herrn Dr. Max Vischer"], "document_number": "letter57"}}, "conversation_id": "9f3fc086-781a-43b7-8131-ca8c9898b86b", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 1, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"gen-1771338178-QLKrFzNhDxbb5fPcZV92\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [\\\"Betrifft Darlehen f\u00fcr den Bau des neuen Personenschiffes.\\\"],\\n \\\"receiver_persons\\\": [\\\"Herrn Dr. Max Vischer\\\"],\\n \\\"send_date\\\": [\\\"1932-10-15\\\"],\\n \\\"sender_persons\\\": [\\\"Basler Rheinschiffahrt Aktiengesellschaft Basel\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1932-10-15\"],\"letter_title\":[\"Betrifft Darlehen f\u00fcr den Bau des neuen Personenschiffes.\"],\"sender_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft Basel\"],\"receiver_persons\":[\"Herrn Dr. Max Vischer\"]}},\"reasoning\":\"So, let's tackle this step by step. I need to extract the required metadata from the historical letter. Let's start by looking at each key: letter_title, sender_persons, send_date, receiver_persons.\\n\\nFirst, the send_date. In the first page, there's a line that says \\\"Basel, den 15.Oktober 1932.\\\" So that's the date. Converting to ISO format: 1932-10-15.\\n\\nNext, receiver_persons. The letter is addressed to \\\"Herrn Dr. Max Vischer, Advokat, Pr\u00e4sident der Personenschiffahrtsgesellschaft, Basel.\\\" So the receiver is Dr. Max Vischer. Also, in the second page, it's repeated: \\\"Herrn Dr. Max Vischer, Advokat, Basel 15.10.32.\\\" So that's the recipient.\\n\\nThen, sender_persons. The letter is from \\\"Basler Rheinschiffahrt Aktiengesellschaft Basel\\\" as seen in the header. Also, the signature at the bottom of the second page is \\\"hochachtend BASEL RHEINSCHIFFFAHRT-AKTIE GESellschaft\\\" with a signature, so the sender is the company. Wait, but the sender_persons field is for the person(s). Wait, in the example, sender_persons is \\\"Lisa Simpson\\\", so it's the individual(s). But here, the sender is the company, so maybe we need to see if there's a specific person. Wait, the company's name is \\\"Basler Rheinschiffahrt Aktiengesellschaft Basel\\\". But in some cases, the company might be the sender, but the problem says \\\"Name(s) of the person(s) who wrote the letter\\\". Wait, but in historical letters, companies might send letters signed by the company. However, the task says \\\"person(s)\\\", so maybe if it's a company, the sender_persons would be the company name? Wait, but in the example, it's a person's name. Wait, maybe in this case, the sender is the company, but the problem says \\\"person(s)\\\", but perhaps the company is considered the sender here. Wait, the instruction says \\\"Name(s) of the person(s) who wrote the letter\\\". But if it's a corporate letter, maybe the company is the sender, but perhaps the sender_persons is the company name as the entity. Wait, looking at the example: \\\"sender_persons\\\": [\\\"Lisa Simpson\\\"], so it's an individual. But in this case, the letter is from a company. Hmm. Wait, the letter has \\\"hochachtend\\\" (with respect) followed by the company name. So the sender is the company. But the question is about the person(s) who wrote the letter. But in corporate letters, it's the company as the sender. However, the task says \\\"person(s)\\\", so maybe in this case, the sender_persons is the company name. Wait, but maybe the company name is the sender. Let's check the first page: the header is \\\"Basler Rheinschiffahrt Aktiengesellschaft Basel * Marktgasse 5\\\", so that's the sender's address. The letter is from that company, so the sender_persons would be the company name. But the instruction says \\\"person(s)\\\", but maybe in historical context, companies are considered the senders, so the name of the company is the sender.\\n\\nNow, letter_title. The letter's subject line is \\\"Betrifft Darlehen f\u00fcr den Bau des neuen Personenschiffes.\\\" So that's the title. So letter_title is [\\\"Betrifft Darlehen f\u00fcr den Bau des neuen Personenschiffes.\\\"].\\n\\nLet's verify each:\\n\\n- send_date: \\\"den 15.Oktober 1932\\\" \u2192 1932-10-15.\\n- receiver_persons: \\\"Herrn Dr. Max Vischer, Advokat, Pr\u00e4sident der Personenschiffahrtsgesellschaft, Basel\\\" \u2192 so the receiver is Dr. Max Vischer. So list with [\\\"Herrn Dr. Max Vischer\\\"] or just \\\"Dr. Max Vischer\\\"? The exact name as per the letter: \\\"Herrn Dr. Max Vischer, Advokat,\\\" so the full name is Herrn Dr. Max Vischer. But maybe in the receiver_persons, it's the name as in the letter. The example has \\\"Mayor Joe Quimby\\\", so probably the full name as written. So \\\"Herrn Dr. Max Vischer\\\" but maybe just \\\"Dr. Max Vischer\\\". Wait, the letter says \\\"Herrn Dr. Max Vischer, Advokat,\\\" so the receiver is Herrn Dr. Max Vischer, so the name is \\\"Dr. Max Vischer\\\" (since \\\"Herrn\\\" is a title, but in the field, we can include it). Wait, the example has \\\"Mayor Joe Quimby\\\", so titles are included. So \\\"Dr. Max Vischer\\\" would be the name. Wait, the letter says \\\"Herrn Dr. Max Vischer\\\", so the receiver is Herrn Dr. Max Vischer. So the receiver_persons should be [\\\"Herrn Dr. Max Vischer\\\"].\\n\\nSender_persons: The sender is Basler Rheinschiffahrt Aktiengesellschaft Basel. But the problem says \\\"person(s)\\\", so maybe the company name is the sender. Wait, but the task says \\\"Name(s) of the person(s) who wrote the letter\\\". But in a corporate letter, the company is the sender, so the sender_persons would be the company name. However, the example has a person's name. Maybe in this case, since it's a company, we include the company name as the sender. So sender_persons: [\\\"Basler Rheinschiffahrt Aktiengesellschaft Basel\\\"].\\n\\nWait, but let's check the header: the first page starts with \\\"Basler Rheinschiffahrt Aktiengesellschaft Basel * Marktgasse 5\\\", which is the sender's address. The letter is from them. So the sender is that company, so the sender_persons would be the company name.\\n\\nNow, letter_title: \\\"Betrifft Darlehen f\u00fcr den Bau des neuen Personenschiffes.\\\" So that's the title.\\n\\nLet's confirm each field:\\n\\n- letter_title: [\\\"Betrifft Darlehen f\u00fcr den Bau des neuen Personenschiffes.\\\"]\\n- send_date: [\\\"1932-10-15\\\"]\\n- sender_persons: [\\\"Basler Rheinschiffahrt Aktiengesellschaft Basel\\\"]\\n- receiver_persons: [\\\"Herrn Dr. Max Vischer\\\"]\\n\\nWait, but in the second page, it's signed by the company, so the sender is the company. So the sender_persons is the company name.\\n\\nLet me check again. The problem says: \\\"Name(s) of the person(s) who wrote the letter\\\". If it's a company, then the company is the sender, so the name would be the company name. Even though it's a company, in historical context, the company is the sender.\\n\\nSo putting it all together.\\n\\nsend_date: 15th October 1932 \u2192 1932-10-15.\\n\\nreceiver_persons: Dr. Max Vischer. The exact text is \\\"Herrn Dr. Max Vischer, Advokat, Pr\u00e4sident der Personenschiffahrtsgesellschaft, Basel\\\". So the recipient is Herrn Dr. Max Vischer. So we can put \\\"Herrn Dr. Max Vischer\\\" as the receiver.\\n\\nsender_persons: The sender is Basler Rheinschiffahrt Aktiengesellschaft Basel. So that's the name of the sender.\\n\\nletter_title: \\\"Betrifft Darlehen f\u00fcr den Bau des neuen Personenschiffes.\\\" \u2192 so that's the title.\\n\\nNow, check if all fields are present. The problem states that if a piece of information is not included, set to \\\"null\\\". But here, all are present.\\n\\nLet's verify each field:\\n\\n- send_date: yes, \\\"den 15.Oktober 1932\\\" \u2192 ISO 1932-10-15.\\n- letter_title: the subject line is \\\"Betrifft Darlehen f\u00fcr den Bau des neuen Personenschiffes.\\\" \u2192 so that's the title.\\n- sender_persons: the company name as the sender.\\n- receiver_persons: Dr. Max Vischer.\\n\\nYes, that seems right.\\n\",\"reasoning_details\":[{\"format\":\"unknown\",\"index\":0,\"type\":\"reasoning.text\",\"text\":\"So, let's tackle this step by step. I need to extract the required metadata from the historical letter. Let's start by looking at each key: letter_title, sender_persons, send_date, receiver_persons.\\n\\nFirst, the send_date. In the first page, there's a line that says \\\"Basel, den 15.Oktober 1932.\\\" So that's the date. Converting to ISO format: 1932-10-15.\\n\\nNext, receiver_persons. The letter is addressed to \\\"Herrn Dr. Max Vischer, Advokat, Pr\u00e4sident der Personenschiffahrtsgesellschaft, Basel.\\\" So the receiver is Dr. Max Vischer. Also, in the second page, it's repeated: \\\"Herrn Dr. Max Vischer, Advokat, Basel 15.10.32.\\\" So that's the recipient.\\n\\nThen, sender_persons. The letter is from \\\"Basler Rheinschiffahrt Aktiengesellschaft Basel\\\" as seen in the header. Also, the signature at the bottom of the second page is \\\"hochachtend BASEL RHEINSCHIFFFAHRT-AKTIE GESellschaft\\\" with a signature, so the sender is the company. Wait, but the sender_persons field is for the person(s). Wait, in the example, sender_persons is \\\"Lisa Simpson\\\", so it's the individual(s). But here, the sender is the company, so maybe we need to see if there's a specific person. Wait, the company's name is \\\"Basler Rheinschiffahrt Aktiengesellschaft Basel\\\". But in some cases, the company might be the sender, but the problem says \\\"Name(s) of the person(s) who wrote the letter\\\". Wait, but in historical letters, companies might send letters signed by the company. However, the task says \\\"person(s)\\\", so maybe if it's a company, the sender_persons would be the company name? Wait, but in the example, it's a person's name. Wait, maybe in this case, the sender is the company, but the problem says \\\"person(s)\\\", but perhaps the company is considered the sender here. Wait, the instruction says \\\"Name(s) of the person(s) who wrote the letter\\\". But if it's a corporate letter, maybe the company is the sender, but perhaps the sender_persons is the company name as the entity. Wait, looking at the example: \\\"sender_persons\\\": [\\\"Lisa Simpson\\\"], so it's an individual. But in this case, the letter is from a company. Hmm. Wait, the letter has \\\"hochachtend\\\" (with respect) followed by the company name. So the sender is the company. But the question is about the person(s) who wrote the letter. But in corporate letters, it's the company as the sender. However, the task says \\\"person(s)\\\", so maybe in this case, the sender_persons is the company name. Wait, but maybe the company name is the sender. Let's check the first page: the header is \\\"Basler Rheinschiffahrt Aktiengesellschaft Basel * Marktgasse 5\\\", so that's the sender's address. The letter is from that company, so the sender_persons would be the company name. But the instruction says \\\"person(s)\\\", but maybe in historical context, companies are considered the senders, so the name of the company is the sender.\\n\\nNow, letter_title. The letter's subject line is \\\"Betrifft Darlehen f\u00fcr den Bau des neuen Personenschiffes.\\\" So that's the title. So letter_title is [\\\"Betrifft Darlehen f\u00fcr den Bau des neuen Personenschiffes.\\\"].\\n\\nLet's verify each:\\n\\n- send_date: \\\"den 15.Oktober 1932\\\" \u2192 1932-10-15.\\n- receiver_persons: \\\"Herrn Dr. Max Vischer, Advokat, Pr\u00e4sident der Personenschiffahrtsgesellschaft, Basel\\\" \u2192 so the receiver is Dr. Max Vischer. So list with [\\\"Herrn Dr. Max Vischer\\\"] or just \\\"Dr. Max Vischer\\\"? The exact name as per the letter: \\\"Herrn Dr. Max Vischer, Advokat,\\\" so the full name is Herrn Dr. Max Vischer. But maybe in the receiver_persons, it's the name as in the letter. The example has \\\"Mayor Joe Quimby\\\", so probably the full name as written. So \\\"Herrn Dr. Max Vischer\\\" but maybe just \\\"Dr. Max Vischer\\\". Wait, the letter says \\\"Herrn Dr. Max Vischer, Advokat,\\\" so the receiver is Herrn Dr. Max Vischer, so the name is \\\"Dr. Max Vischer\\\" (since \\\"Herrn\\\" is a title, but in the field, we can include it). Wait, the example has \\\"Mayor Joe Quimby\\\", so titles are included. So \\\"Dr. Max Vischer\\\" would be the name. Wait, the letter says \\\"Herrn Dr. Max Vischer\\\", so the receiver is Herrn Dr. Max Vischer. So the receiver_persons should be [\\\"Herrn Dr. Max Vischer\\\"].\\n\\nSender_persons: The sender is Basler Rheinschiffahrt Aktiengesellschaft Basel. But the problem says \\\"person(s)\\\", so maybe the company name is the sender. Wait, but the task says \\\"Name(s) of the person(s) who wrote the letter\\\". But in a corporate letter, the company is the sender, so the sender_persons would be the company name. However, the example has a person's name. Maybe in this case, since it's a company, we include the company name as the sender. So sender_persons: [\\\"Basler Rheinschiffahrt Aktiengesellschaft Basel\\\"].\\n\\nWait, but let's check the header: the first page starts with \\\"Basler Rheinschiffahrt Aktiengesellschaft Basel * Marktgasse 5\\\", which is the sender's address. The letter is from them. So the sender is that company, so the sender_persons would be the company name.\\n\\nNow, letter_title: \\\"Betrifft Darlehen f\u00fcr den Bau des neuen Personenschiffes.\\\" So that's the title.\\n\\nLet's confirm each field:\\n\\n- letter_title: [\\\"Betrifft Darlehen f\u00fcr den Bau des neuen Personenschiffes.\\\"]\\n- send_date: [\\\"1932-10-15\\\"]\\n- sender_persons: [\\\"Basler Rheinschiffahrt Aktiengesellschaft Basel\\\"]\\n- receiver_persons: [\\\"Herrn Dr. Max Vischer\\\"]\\n\\nWait, but in the second page, it's signed by the company, so the sender is the company. So the sender_persons is the company name.\\n\\nLet me check again. The problem says: \\\"Name(s) of the person(s) who wrote the letter\\\". If it's a company, then the company is the sender, so the name would be the company name. Even though it's a company, in historical context, the company is the sender.\\n\\nSo putting it all together.\\n\\nsend_date: 15th October 1932 \u2192 1932-10-15.\\n\\nreceiver_persons: Dr. Max Vischer. The exact text is \\\"Herrn Dr. Max Vischer, Advokat, Pr\u00e4sident der Personenschiffahrtsgesellschaft, Basel\\\". So the recipient is Herrn Dr. Max Vischer. So we can put \\\"Herrn Dr. Max Vischer\\\" as the receiver.\\n\\nsender_persons: The sender is Basler Rheinschiffahrt Aktiengesellschaft Basel. So that's the name of the sender.\\n\\nletter_title: \\\"Betrifft Darlehen f\u00fcr den Bau des neuen Personenschiffes.\\\" \u2192 so that's the title.\\n\\nNow, check if all fields are present. The problem states that if a piece of information is not included, set to \\\"null\\\". But here, all are present.\\n\\nLet's verify each field:\\n\\n- send_date: yes, \\\"den 15.Oktober 1932\\\" \u2192 ISO 1932-10-15.\\n- letter_title: the subject line is \\\"Betrifft Darlehen f\u00fcr den Bau des neuen Personenschiffes.\\\" \u2192 so that's the title.\\n- sender_persons: the company name as the sender.\\n- receiver_persons: Dr. Max Vischer.\\n\\nYes, that seems right.\\n\"}]},\"native_finish_reason\":\"stop\"}],\"created\":1771338178,\"model\":\"qwen/qwen3-vl-8b-thinking\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":1916,\"prompt_tokens\":5633,\"total_tokens\":7549,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":1826,\"rejected_prediction_tokens\":null},\"prompt_tokens_details\":{\"audio_tokens\":null,\"cached_tokens\":0},\"cost\":0.003274401,\"is_byok\":false,\"cost_details\":{\"upstream_inference_cost\":0.00503754,\"upstream_inference_prompt_cost\":0.00101394,\"upstream_inference_completions_cost\":0.0040236}},\"provider\":\"Alibaba\"}"}, "scoring": {"f1_macro": 0.48, "f1_micro": 0.48, "cost_summary": {"total_input_tokens": 280729, "total_output_tokens": 151473, "total_tokens": 432202, "input_cost_usd": 0.050531220000000036, "output_cost_usd": 0.3180933000000001, "total_cost_usd": 0.36862451999999996}}, "normalized_score": 48.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c6b"}, "test_id": "T0109", "benchmark": "business_letters", "date": "2026-02-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1938-07-14\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"null\"]}}", "model": "gpt-5-2025-08-07", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 1398, "output_tokens": 1326, "total_tokens": 2724, "input_cost_usd": 0.0017475, "output_cost_usd": 0.01326, "estimated_cost_usd": 0.0150075}, "duration": 28.024263858795166, "timestamp": "2026-02-17T11:52:30.794443", "parsed": {"metadata": {"send_date": ["1938-07-14"], "letter_title": ["null"], "sender_persons": ["null"], "receiver_persons": ["null"], "document_number": "letter11"}}, "conversation_id": "ff7a7a55-6822-4206-b4df-9e4dffeb3f33", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-DACyRZb2M4xMaqLCGcT6qUC9U2q7P\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1938-07-14\\\"],\\\"letter_title\\\":[\\\"null\\\"],\\\"sender_persons\\\":[\\\"null\\\"],\\\"receiver_persons\\\":[\\\"null\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1938-07-14\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"null\"]}}}}],\"created\":1771325523,\"model\":\"gpt-5-2025-08-07\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":1326,\"prompt_tokens\":1398,\"total_tokens\":2724,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":1280,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.81, "f1_micro": 0.87, "cost_summary": {"total_input_tokens": 44050, "total_output_tokens": 37531, "total_tokens": 81581, "input_cost_usd": 0.05506249999999998, "output_cost_usd": 0.37531, "total_cost_usd": 0.43037250000000005}}, "normalized_score": 81.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c6c"}, "test_id": "T0190", "benchmark": "business_letters", "date": "2026-02-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-large-2411", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":null,\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":null}}", "model": "mistral-large-2411", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 640, "output_tokens": 51, "total_tokens": 691, "input_cost_usd": 0.00128, "output_cost_usd": 0.000306, "estimated_cost_usd": 0.0015860000000000002}, "duration": 1.3129463195800781, "timestamp": "2026-02-17T14:46:45.696758", "parsed": {"metadata": {"letter_title": null, "send_date": null, "sender_persons": null, "receiver_persons": null, "document_number": "letter09"}}, "conversation_id": "f7392b57-22ae-400c-b2ec-ebe302de69cd", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"3dda37739ce641dca05ff08c1941becf\",\"object\":\"chat.completion\",\"model\":\"mistral-large-2411\",\"usage\":{\"prompt_tokens\":640,\"completion_tokens\":51,\"total_tokens\":691,\"prompt_tokens_details\":{\"cached_tokens\":640}},\"created\":1771336004,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"send_date\\\": null,\\n \\\"sender_persons\\\": null,\\n \\\"receiver_persons\\\": null\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 20480, "total_output_tokens": 1594, "total_tokens": 22074, "input_cost_usd": 0.040960000000000024, "output_cost_usd": 0.009564000000000001, "total_cost_usd": 0.05052399999999998}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718c68"}, "test_id": "T0061", "benchmark": "business_letters", "date": "2026-02-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "pixtral-large-2411", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":null,\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":null}}", "model": "pixtral-large-2411", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 640, "output_tokens": 56, "total_tokens": 696, "input_cost_usd": 0.00128, "output_cost_usd": 0.000336, "estimated_cost_usd": 0.001616}, "duration": 1.1423425674438477, "timestamp": "2026-02-17T13:42:45.634998", "parsed": {"metadata": {"letter_title": null, "send_date": null, "sender_persons": null, "receiver_persons": null, "document_number": "letter42"}}, "conversation_id": "f7a3787b-fab2-416a-80dd-5d428c6c9202", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"1f2df8ccb2ce43ff84e91fbd39862aed\",\"object\":\"chat.completion\",\"model\":\"pixtral-large-2411\",\"usage\":{\"prompt_tokens\":640,\"completion_tokens\":56,\"total_tokens\":696,\"prompt_tokens_details\":{\"cached_tokens\":640}},\"created\":1771332164,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [null],\\n \\\"send_date\\\": [null],\\n \\\"sender_persons\\\": [null],\\n \\\"receiver_persons\\\": [null]\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 20480, "total_output_tokens": 1792, "total_tokens": 22272, "input_cost_usd": 0.040960000000000024, "output_cost_usd": 0.010752, "total_cost_usd": 0.05171199999999999}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718c65"}, "test_id": "T0426", "benchmark": "business_letters", "date": "2026-02-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "magistral-medium-2509", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":null,\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":null}}", "model": "magistral-medium-2509", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 44, "total_tokens": 629, "input_cost_usd": 0.00117, "output_cost_usd": 0.00021999999999999998, "estimated_cost_usd": 0.00139}, "duration": 2.450777530670166, "timestamp": "2026-02-17T15:45:18.376417", "parsed": {"metadata": {"letter_title": null, "send_date": null, "sender_persons": null, "receiver_persons": null, "document_number": "letter26"}}, "conversation_id": "cdc5b38b-51af-4ebb-9953-1506fd1e3eea", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"09f08ca8002a429ea1fb2e719516b8ae\",\"object\":\"chat.completion\",\"model\":\"magistral-medium-2509\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":44,\"total_tokens\":629,\"prompt_tokens_details\":{\"cached_tokens\":704}},\"created\":1771339516,\"choices\":[{\"index\":0,\"message\":{\"content\":\" {\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"send_date\\\": null,\\n \\\"sender_persons\\\": null,\\n \\\"receiver_persons\\\": null\\n }\\n }\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 33345, "total_output_tokens": 2508, "total_tokens": 35853, "input_cost_usd": 0.06668999999999996, "output_cost_usd": 0.01253999999999999, "total_cost_usd": 0.07923000000000006}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718c64"}, "test_id": "T0250", "benchmark": "business_letters", "date": "2026-02-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "meta-llama/llama-4-maverick", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-10-15\"],\"letter_title\":[\"Betrifft Darlehen f\u00fcr den Bau des neuen Personenschiffes\"],\"sender_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft\"],\"receiver_persons\":[\"Dr. Max Vischer, Advokat, Pr\u00e4sident der Personenschiffahrtsgesellschaft, Basel\"]}}", "model": "meta-llama/llama-4-maverick", "provider": "openrouter", "finish_reason": "stop", "usage": {"input_tokens": 4968, "output_tokens": 89, "total_tokens": 5057, "input_cost_usd": 0.0007452, "output_cost_usd": 5.34e-05, "estimated_cost_usd": 0.0007986}, "duration": 3.3442742824554443, "timestamp": "2026-02-17T15:23:37.390816", "parsed": {"metadata": {"send_date": ["1932-10-15"], "letter_title": ["Betrifft Darlehen f\u00fcr den Bau des neuen Personenschiffes"], "sender_persons": ["Basler Rheinschiffahrt Aktiengesellschaft"], "receiver_persons": ["Dr. Max Vischer, Advokat, Pr\u00e4sident der Personenschiffahrtsgesellschaft, Basel"], "document_number": "letter57"}}, "conversation_id": "32c00a4b-0692-419a-8f3d-f7b58e55d370", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"gen-1771338214-0ZbTibsl9NRKN0kiQOqR\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1932-10-15\\\"],\\n \\\"letter_title\\\": [\\\"Betrifft Darlehen f\u00fcr den Bau des neuen Personenschiffes\\\"],\\n \\\"sender_persons\\\": [\\\"Basler Rheinschiffahrt Aktiengesellschaft\\\"],\\n \\\"receiver_persons\\\": [\\\"Dr. Max Vischer, Advokat, Pr\u00e4sident der Personenschiffahrtsgesellschaft, Basel\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1932-10-15\"],\"letter_title\":[\"Betrifft Darlehen f\u00fcr den Bau des neuen Personenschiffes\"],\"sender_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft\"],\"receiver_persons\":[\"Dr. Max Vischer, Advokat, Pr\u00e4sident der Personenschiffahrtsgesellschaft, Basel\"]}},\"reasoning\":null},\"native_finish_reason\":\"stop\"}],\"created\":1771338214,\"model\":\"meta-llama/llama-4-maverick\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":89,\"prompt_tokens\":4968,\"total_tokens\":5057,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":null},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0},\"cost\":0.00141701,\"is_byok\":false,\"cost_details\":{\"upstream_inference_cost\":0.00141701,\"upstream_inference_prompt_cost\":0.00134136,\"upstream_inference_completions_cost\":0.00007565}},\"provider\":\"Together\"}"}, "scoring": {"f1_macro": 0.54, "f1_micro": 0.5, "cost_summary": {"total_input_tokens": 156873, "total_output_tokens": 2005, "total_tokens": 158878, "input_cost_usd": 0.023530950000000005, "output_cost_usd": 0.001203, "total_cost_usd": 0.024733949999999998}}, "normalized_score": 54.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c70"}, "test_id": "T0248", "benchmark": "business_letters", "date": "2026-02-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "meta-llama/llama-4-maverick", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-05-05\"],\"letter_title\":[\"\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"Basler Rheinschiffahrts-A.G.\"]}}", "model": "meta-llama/llama-4-maverick", "provider": "openrouter", "finish_reason": "stop", "usage": {"input_tokens": 2645, "output_tokens": 49, "total_tokens": 2694, "input_cost_usd": 0.00039675, "output_cost_usd": 2.9399999999999996e-05, "estimated_cost_usd": 0.00042615000000000003}, "duration": 2.712932586669922, "timestamp": "2026-02-17T15:23:48.829849", "parsed": {"metadata": {"send_date": ["1928-05-05"], "letter_title": [""], "sender_persons": ["null"], "receiver_persons": ["Basler Rheinschiffahrts-A.G."], "document_number": "letter33"}}, "conversation_id": "b6f7fdf1-46f1-45ad-923f-09635424b5a2", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"gen-1771338226-2P0hN4nShONboGx81jHG\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\": {\\\"send_date\\\": [\\\"1928-05-05\\\"], \\\"letter_title\\\": [\\\"\\\"], \\\"sender_persons\\\": [\\\"null\\\"], \\\"receiver_persons\\\": [\\\"Basler Rheinschiffahrts-A.G.\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-05-05\"],\"letter_title\":[\"\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"Basler Rheinschiffahrts-A.G.\"]}},\"reasoning\":null},\"native_finish_reason\":\"stop\"}],\"created\":1771338226,\"model\":\"meta-llama/llama-4-maverick\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":49,\"prompt_tokens\":2645,\"total_tokens\":2694,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":null},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0},\"cost\":0.00042615,\"is_byok\":false,\"cost_details\":{\"upstream_inference_cost\":0.00042615,\"upstream_inference_prompt_cost\":0.00039675,\"upstream_inference_completions_cost\":0.0000294}},\"provider\":\"DeepInfra\"}"}, "scoring": {"f1_macro": 0.52, "f1_micro": 0.53, "cost_summary": {"total_input_tokens": 246251, "total_output_tokens": 3579, "total_tokens": 249830, "input_cost_usd": 0.03693765000000002, "output_cost_usd": 0.0021473999999999994, "total_cost_usd": 0.03908505}}, "normalized_score": 52.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c74"}, "test_id": "T0534", "benchmark": "business_letters", "date": "2026-02-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-large-2512", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\n \"metadata\": {\n \"letter_title\": [null],\n \"send_date\": [null],\n \"sender_persons\": [null],\n \"receiver_persons\": [null]\n }\n}", "model": "mistral-large-2512", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 46, "total_tokens": 631, "input_cost_usd": 0.0002925, "output_cost_usd": 6.9e-05, "estimated_cost_usd": 0.0003615}, "duration": 1.0304346084594727, "timestamp": "2026-02-17T15:49:22.487591", "parsed": {"metadata": {"letter_title": [null], "send_date": [null], "sender_persons": [null], "receiver_persons": [null], "document_number": "letter49"}}, "conversation_id": "765e0c65-391c-4b6c-b488-6da97c181334", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"4d755dce1f8e46a7b8a2d2e7c346d1b3\",\"object\":\"chat.completion\",\"model\":\"mistral-large-2512\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":46,\"total_tokens\":631,\"prompt_tokens_details\":{\"cached_tokens\":592}},\"created\":1771339761,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [null],\\n \\\"send_date\\\": [null],\\n \\\"sender_persons\\\": [null],\\n \\\"receiver_persons\\\": [null]\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 14625, "total_output_tokens": 1082, "total_tokens": 15707, "input_cost_usd": 0.007312500000000004, "output_cost_usd": 0.0016229999999999997, "total_cost_usd": 0.008935499999999999}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718c66"}, "test_id": "T0249", "benchmark": "business_letters", "date": "2026-02-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "meta-llama/llama-4-maverick", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-09-23\"],\"letter_title\":[\"\"],\"sender_persons\":[\"Basler Rheinschiffahrts Aktiengesellschaft\"],\"receiver_persons\":[\"Direktion Basel, Marktgasse 5\"]}}", "model": "meta-llama/llama-4-maverick", "provider": "openrouter", "finish_reason": "stop", "usage": {"input_tokens": 2649, "output_tokens": 58, "total_tokens": 2707, "cached_tokens": 320, "input_cost_usd": 0.00039735, "output_cost_usd": 3.48e-05, "estimated_cost_usd": 0.00043214999999999996}, "duration": 2.4427051544189453, "timestamp": "2026-02-17T15:23:28.278717", "parsed": {"metadata": {"send_date": ["1932-09-23"], "letter_title": [""], "sender_persons": ["Basler Rheinschiffahrts Aktiengesellschaft"], "receiver_persons": ["Direktion Basel, Marktgasse 5"], "document_number": "letter51"}}, "conversation_id": "a0cbcc7a-887f-416a-9eb9-6fcf044ff19c", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"gen-1771338206-QYKXA4J2BhPnc4ELmsvR\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\": {\\\"send_date\\\": [\\\"1932-09-23\\\"], \\\"letter_title\\\": [\\\"\\\"], \\\"sender_persons\\\": [\\\"Basler Rheinschiffahrts Aktiengesellschaft\\\"], \\\"receiver_persons\\\": [\\\"Direktion Basel, Marktgasse 5\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1932-09-23\"],\"letter_title\":[\"\"],\"sender_persons\":[\"Basler Rheinschiffahrts Aktiengesellschaft\"],\"receiver_persons\":[\"Direktion Basel, Marktgasse 5\"]}},\"reasoning\":null},\"native_finish_reason\":\"stop\"}],\"created\":1771338206,\"model\":\"meta-llama/llama-4-maverick\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":58,\"prompt_tokens\":2649,\"total_tokens\":2707,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":null},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":320},\"cost\":0.00098515,\"is_byok\":false,\"cost_details\":{\"upstream_inference_cost\":0.00098515,\"upstream_inference_prompt_cost\":0.00092715,\"upstream_inference_completions_cost\":0.000058}},\"provider\":\"Parasail\"}"}, "scoring": {"f1_macro": 0.45, "f1_micro": 0.55, "cost_summary": {"total_input_tokens": 89367, "total_output_tokens": 1537, "total_tokens": 90904, "input_cost_usd": 0.013405049999999998, "output_cost_usd": 0.0009221999999999998, "total_cost_usd": 0.01432725}}, "normalized_score": 45.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c76"}, "test_id": "T0533", "benchmark": "business_letters", "date": "2026-02-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-large-2512", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\n \"metadata\": {\n \"letter_title\": [null],\n \"send_date\": [null],\n \"sender_persons\": [null],\n \"receiver_persons\": [null]\n }\n}", "model": "mistral-large-2512", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 46, "total_tokens": 631, "input_cost_usd": 0.0002925, "output_cost_usd": 6.9e-05, "estimated_cost_usd": 0.0003615}, "duration": 1.051697015762329, "timestamp": "2026-02-17T15:47:55.095820", "parsed": {"metadata": {"letter_title": [null], "send_date": [null], "sender_persons": [null], "receiver_persons": [null], "document_number": "letter21"}}, "conversation_id": "9d779b19-0e04-4eed-9349-a6eb40b3f32a", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"8778dd36db2a48c49309c15a2def9bf1\",\"object\":\"chat.completion\",\"model\":\"mistral-large-2512\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":46,\"total_tokens\":631,\"prompt_tokens_details\":{\"cached_tokens\":592}},\"created\":1771339674,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [null],\\n \\\"send_date\\\": [null],\\n \\\"sender_persons\\\": [null],\\n \\\"receiver_persons\\\": [null]\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 33345, "total_output_tokens": 2526, "total_tokens": 35871, "input_cost_usd": 0.01667249999999999, "output_cost_usd": 0.003789000000000002, "total_cost_usd": 0.020461500000000018}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718c79"}, "test_id": "T0428", "benchmark": "business_letters", "date": "2026-02-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "magistral-medium-2509", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":null,\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":null}}", "model": "magistral-medium-2509", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 44, "total_tokens": 629, "input_cost_usd": 0.00117, "output_cost_usd": 0.00021999999999999998, "estimated_cost_usd": 0.00139}, "duration": 1.4024879932403564, "timestamp": "2026-02-17T15:43:54.002388", "parsed": {"metadata": {"letter_title": null, "send_date": null, "sender_persons": null, "receiver_persons": null, "document_number": "letter53"}}, "conversation_id": "59634b26-cbe4-4450-828b-57f71470d11f", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"2580d8ddef40491387e403e7921d2aa8\",\"object\":\"chat.completion\",\"model\":\"magistral-medium-2509\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":44,\"total_tokens\":629,\"prompt_tokens_details\":{\"cached_tokens\":704}},\"created\":1771339432,\"choices\":[{\"index\":0,\"message\":{\"content\":\" {\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"send_date\\\": null,\\n \\\"sender_persons\\\": null,\\n \\\"receiver_persons\\\": null\\n }\\n }\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 18720, "total_output_tokens": 1408, "total_tokens": 20128, "input_cost_usd": 0.03744, "output_cost_usd": 0.007039999999999997, "total_cost_usd": 0.04448000000000001}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718c58"}, "test_id": "T0109", "benchmark": "business_letters", "date": "2026-02-10", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-07-14\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":null}}", "model": "gpt-5-2025-08-07", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 1398, "output_tokens": 1643, "total_tokens": 3041, "input_cost_usd": 0.0017475, "output_cost_usd": 0.01643, "estimated_cost_usd": 0.0181775}, "duration": 49.13663339614868, "timestamp": "2026-02-10T13:10:06.052884", "parsed": {"metadata": {"send_date": ["1928-07-14"], "letter_title": null, "sender_persons": null, "receiver_persons": null, "document_number": "letter11"}}, "conversation_id": "488ac4d5-cfa8-4747-94ed-80639e4f92d0", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D7gqNEgzXY8jsLZRGqJDNhYgsxcLT\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1928-07-14\\\"],\\\"letter_title\\\":null,\\\"sender_persons\\\":null,\\\"receiver_persons\\\":null}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-07-14\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":null}}}}],\"created\":1770725359,\"model\":\"gpt-5-2025-08-07\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":1643,\"prompt_tokens\":1398,\"total_tokens\":3041,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":1600,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.71, "f1_micro": 0.78, "cost_summary": {"total_input_tokens": 44050, "total_output_tokens": 41795, "total_tokens": 85845, "input_cost_usd": 0.05506249999999998, "output_cost_usd": 0.41795000000000004, "total_cost_usd": 0.47301249999999995}}, "normalized_score": 71.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c59"}, "test_id": "T0113", "benchmark": "business_letters", "date": "2026-02-10", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-11-24\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"Dr Max Vischer\",\"Dr P. C. von Planta\"],\"receiver_persons\":[\"A. Oettinger\"]}}", "model": "gpt-5-mini-2025-08-07", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 2256, "output_tokens": 1021, "total_tokens": 3277, "input_cost_usd": 0.000564, "output_cost_usd": 0.002042, "estimated_cost_usd": 0.002606}, "duration": 26.965296983718872, "timestamp": "2026-02-10T13:39:08.638525", "parsed": {"metadata": {"send_date": ["1932-11-24"], "letter_title": ["null"], "sender_persons": ["Dr Max Vischer", "Dr P. C. von Planta"], "receiver_persons": ["A. Oettinger"], "document_number": "letter58"}}, "conversation_id": "81068081-be6c-4e01-9b72-b91181d69657", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 2, "sender_persons_fn": 1, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D7hIpKo8n3yTljRKHlBWHZEjqunp4\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1932-11-24\\\"],\\\"letter_title\\\":[\\\"null\\\"],\\\"sender_persons\\\":[\\\"Dr Max Vischer\\\",\\\"Dr P. C. von Planta\\\"],\\\"receiver_persons\\\":[\\\"A. Oettinger\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1932-11-24\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"Dr Max Vischer\",\"Dr P. C. von Planta\"],\"receiver_persons\":[\"A. Oettinger\"]}}}}],\"created\":1770727123,\"model\":\"gpt-5-mini-2025-08-07\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":1021,\"prompt_tokens\":2256,\"total_tokens\":3277,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":960,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.57, "f1_micro": 0.53, "cost_summary": {"total_input_tokens": 127000, "total_output_tokens": 31815, "total_tokens": 158815, "input_cost_usd": 0.03174999999999999, "output_cost_usd": 0.06362999999999999, "total_cost_usd": 0.09538}}, "normalized_score": 56.99999999999999}, {"_id": {"$oid": "69d4eb12b877594bc5718c2f"}, "test_id": "T0112", "benchmark": "business_letters", "date": "2026-01-26", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-08-13\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\",\"Groschopf\",\"J.A. Ritter\"],\"receiver_persons\":[\"Dr. Max Vischer\",\"Basler Personenschiffahrtsgesellschaft\"]}}", "model": "gpt-5-mini-2025-08-07", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 5792, "output_tokens": 1075, "total_tokens": 6867, "input_cost_usd": 0.001448, "output_cost_usd": 0.00215, "estimated_cost_usd": 0.003598}, "duration": 20.509827852249146, "timestamp": "2026-01-26T23:47:46.679341", "parsed": {"metadata": {"send_date": ["1926-08-13"], "letter_title": ["null"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft", "Groschopf", "J.A. Ritter"], "receiver_persons": ["Dr. Max Vischer", "Basler Personenschiffahrtsgesellschaft"], "document_number": "letter12"}}, "conversation_id": "c412392d-085a-41cf-81a3-9bbd24382805", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 2, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 1, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D2Pej06DowYftKYjbkbfMixswYC0e\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1926-08-13\\\"\\n ],\\n \\\"letter_title\\\": [\\n \\\"null\\\"\\n ],\\n \\\"sender_persons\\\": [\\n \\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\",\\n \\\"Groschopf\\\",\\n \\\"J.A. Ritter\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Dr. Max Vischer\\\",\\n \\\"Basler Personenschiffahrtsgesellschaft\\\"\\n ]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1926-08-13\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\",\"Groschopf\",\"J.A. Ritter\"],\"receiver_persons\":[\"Dr. Max Vischer\",\"Basler Personenschiffahrtsgesellschaft\"]}}}}],\"created\":1769467649,\"model\":\"gpt-5-mini-2025-08-07\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":1075,\"prompt_tokens\":5792,\"total_tokens\":6867,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":960,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.49, "f1_micro": 0.56, "cost_summary": {"total_input_tokens": 74080, "total_output_tokens": 24391, "total_tokens": 98471, "input_cost_usd": 0.018519999999999995, "output_cost_usd": 0.048782, "total_cost_usd": 0.067302}}, "normalized_score": 49.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c0f"}, "test_id": "T0135", "benchmark": "business_letters", "date": "2026-01-26", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "o3", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-03-29\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":[\"Dr. W. Krasting\"]}}", "model": "o3-2025-04-16", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 1463, "output_tokens": 250, "total_tokens": 1713, "input_cost_usd": 0.002926, "output_cost_usd": 0.002, "estimated_cost_usd": 0.004926}, "duration": 8.939486503601074, "timestamp": "2026-01-26T23:38:49.513007", "parsed": {"metadata": {"send_date": ["1926-03-29"], "letter_title": null, "sender_persons": null, "receiver_persons": ["Dr. W. Krasting"], "document_number": "letter05"}}, "conversation_id": "e957e428-3733-4d1c-8b0f-73fcd9018692", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D2PWDGCbzNdEjXwX5YqCOReqXcdeF\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1926-03-29\\\"],\\\"letter_title\\\":null,\\\"sender_persons\\\":null,\\\"receiver_persons\\\":[\\\"Dr. W. Krasting\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1926-03-29\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":[\"Dr. W. Krasting\"]}}}}],\"created\":1769467121,\"model\":\"o3-2025-04-16\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":250,\"prompt_tokens\":1463,\"total_tokens\":1713,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":192,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.67, "f1_micro": 0.77, "cost_summary": {"total_input_tokens": 46325, "total_output_tokens": 15692, "total_tokens": 62017, "input_cost_usd": 0.09265, "output_cost_usd": 0.125536, "total_cost_usd": 0.21818600000000002}}, "normalized_score": 67.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c2d"}, "test_id": "T0110", "benchmark": "business_letters", "date": "2026-01-26", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-06-22\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":[\"P. Christ-Wackernagel\"]}}", "model": "gpt-5-2025-08-07", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 1398, "output_tokens": 1464, "total_tokens": 2862, "input_cost_usd": 0.0017475, "output_cost_usd": 0.01464, "estimated_cost_usd": 0.0163875}, "duration": 80.11324119567871, "timestamp": "2026-01-26T23:05:35.514767", "parsed": {"metadata": {"send_date": ["1926-06-22"], "letter_title": null, "sender_persons": null, "receiver_persons": ["P. Christ-Wackernagel"], "document_number": "letter07"}}, "conversation_id": "7fce53e6-e816-403f-aa58-ec42d6dc6337", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D2OyuAe1OdNNQz3MZ3KP2SeEA35wg\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\": {\\\"send_date\\\": [\\\"1926-06-22\\\"], \\\"letter_title\\\": null, \\\"sender_persons\\\": null, \\\"receiver_persons\\\": [\\\"P. Christ-Wackernagel\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1926-06-22\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":[\"P. Christ-Wackernagel\"]}}}}],\"created\":1769465056,\"model\":\"gpt-5-2025-08-07\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":1464,\"prompt_tokens\":1398,\"total_tokens\":2862,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":1408,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.64, "f1_micro": 0.64, "cost_summary": {"total_input_tokens": 72946, "total_output_tokens": 63241, "total_tokens": 136187, "input_cost_usd": 0.09118249999999997, "output_cost_usd": 0.6324100000000001, "total_cost_usd": 0.7235924999999999}}, "normalized_score": 64.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c1d"}, "test_id": "T0555", "benchmark": "business_letters", "date": "2026-01-26", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "ministral-8b-2512", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":null,\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":null}}", "model": "ministral-8b-2512", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 42, "total_tokens": 627, "input_cost_usd": 8.775e-05, "output_cost_usd": 6.3e-06, "estimated_cost_usd": 9.405000000000001e-05}, "duration": 0.7906451225280762, "timestamp": "2026-01-26T23:01:55.742027", "parsed": {"metadata": {"letter_title": null, "sender_persons": null, "send_date": null, "receiver_persons": null, "document_number": "letter01"}}, "conversation_id": "760fe8d6-cb4a-4c7f-b346-eef545e9a567", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"387d30ac685d47da9ba19f9e55eb2e12\",\"object\":\"chat.completion\",\"model\":\"ministral-8b-2512\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":42,\"total_tokens\":627,\"num_cached_tokens\":0},\"created\":1769464915,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"sender_persons\\\": null,\\n \\\"send_date\\\": null,\\n \\\"receiver_persons\\\": null\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": null, "normalized_score": null}, {"_id": {"$oid": "69d4eb12b877594bc5718c13"}, "test_id": "T0244", "benchmark": "business_letters", "date": "2026-01-26", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "qwen/qwen3-vl-8b-thinking", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-03-29\"],\"letter_title\":[\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\"],\"sender_persons\":null,\"receiver_persons\":[\"Dr. W. Krasting\"]}}", "model": "qwen/qwen3-vl-8b-thinking", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 1847, "output_tokens": 8580, "total_tokens": 10427}, "duration": 109.25542044639587, "timestamp": "2026-01-26T23:04:59.044703", "parsed": {"metadata": {"send_date": ["1926-03-29"], "letter_title": ["Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926"], "sender_persons": null, "receiver_persons": ["Dr. W. Krasting"], "document_number": "letter05"}}, "conversation_id": "02d35714-0108-449d-9931-98994828249f", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"gen-1769464990-N9LbaXYep4mJioqQzl8s\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [\\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\"],\\n \\\"receiver_persons\\\": [\\\"Dr. W. Krasting\\\"],\\n \\\"send_date\\\": [\\\"1926-03-29\\\"],\\n \\\"sender_persons\\\": null\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1926-03-29\"],\"letter_title\":[\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\"],\"sender_persons\":null,\"receiver_persons\":[\"Dr. W. Krasting\"]}},\"reasoning\":\"Okay, let's tackle this problem step by step. So, I need to extract specific information from a historical letter and format it into a JSON according to the given schema. Let me start by understanding what exactly is required.\\n\\nFirst, the user provided a JSON schema that defines the structure of the output. The main object should have a \\\"metadata\\\" key, which is an object containing four required fields: letter_title, sender_persons, send_date, and receiver_persons. Each of these fields should be a list, even if there's only one value. If a field isn't present in the letter, it should be \\\"null\\\". The date must be in ISO format (YYYY-MM-DD), and the sender/receiver names should be in arrays.\\n\\nNow, looking at the letter image description. The user mentioned it's a historical letter from 1926, so I need to parse the details from the provided text. Wait, the actual image content isn't here; instead, there's a text description of the letter. Let me check the example given in the problem statement.\\n\\nThe example shows a JSON with example values. But the user provided a specific letter description here. Let me read the letter details again.\\n\\nThe letter starts with \\\"Basel, den 29.M\u00e4rz 1926.\\\" So the date is 29th March 1926. Need to convert that to ISO format. March is the 3rd month, so 1926-03-29.\\n\\nNext, the sender_persons. The letter is addressed to \\\"Herrn Dr. W. Krasting,\\\" and the sender seems to be someone at the \\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926.\\\" But wait, the sender's name isn't explicitly stated here. Wait, in the letter, the salutation is \\\"Herrn Dr. W. Krasting,\\\" which is the recipient. The sender's name isn't directly written out. However, the text mentions \\\"Ich best\u00e4tige Ihnen dankend den Erhalt Ihres Schreibens vom 26. dies...\\\" so the sender is probably someone from the organization mentioned. But the problem says to extract the sender_persons from the letter.\\n\\nWait, in the letter, the closing is \\\"Hochachtungsvoll,\\\" which is a common closing for formal letters, but the sender's name isn't listed. Wait, maybe there's a mistake here. Let me check again.\\n\\nLooking at the provided text:\\n\\n\\\"Basel, den 29.M\u00e4rz 1926.\\n\\nT\\n\\nHerrn Dr. W. Krasting,\\n\\nInternationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\n\\nBasel.\\n\\nIch best\u00e4tige Ihnen dankend den Erhalt Ihres Schreibens vom 26. dies und teile Ihnen mit, dass die Besprechungen mit verschiedenen unserer Vorstandsmitglieder wegen einer Betriebsgemeinschaft weiter gef\u00fchrt werden. Ich glaube, dass wir n\u00e4chstens mit einem Vorschlag werden an Sie herantreten k\u00f6nnen.\\n\\nHochachtungsvoll\\\"\\n\\nWait, the sender's name isn't present in the visible text. The letter is addressed to Herr Dr. W. Krasting, and the sender might be implied to be a representative of the International Exhibition. But the problem states to extract the sender_persons from the letter. Since the sender's name isn't explicitly mentioned here, maybe it's \\\"null\\\"?\\n\\nBut wait, the example shows sender_persons as [\\\"Lisa Simpson\\\"], so maybe in some cases the sender is known. Let me check the content again.\\n\\nThe letter says \\\"Ich best\u00e4tige Ihnen...\\\", which translates to \\\"I confirm to you...\\\" So the sender is the person writing the letter. However, the sender's name isn't written out in the letter. The only mention is the organization name: \\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\". But the problem says to extract the person's name(s). If the sender's name isn't written, then it would be \\\"null\\\". But maybe the organization's name is considered the sender? But the instructions specify \\\"Name(s) of the person(s)\\\", so perhaps it's not the organization.\\n\\nWait, in formal letters, sometimes the sender's name isn't written but is part of the organization. But according to the problem statement, the sender_persons should be the person(s) who wrote the letter. If the letter is from the organization, maybe the sender_persons are the organization's representatives, but since we don't have individual names, perhaps it's \\\"null\\\".\\n\\nWait, but the problem says \\\"If a piece of information is not included in the letter, set the value for the corresponding key to 'null'.\\\"\\n\\nSo if the sender's name is not present, it's \\\"null\\\".\\n\\nSimilarly, receiver_persons is \\\"Herrn Dr. W. Krasting\\\", which would be [\\\"Dr. W. Krasting\\\"].\\n\\nLetter title: The title might be the subject line or the main topic. The letter mentions \\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\", which is the name of the exhibition. So perhaps the letter title is related to that.\\n\\nBut the example shows a title like \\\"Petition for Environmental Protection\\\". So the letter_title would be the main subject. Let me check the content.\\n\\nThe letter says: \\\"Ich best\u00e4tige Ihnen dankend den Erhalt Ihres Schreibens vom 26. dies und teile Ihnen mit, dass die Besprechungen mit verschiedenen unserer Vorstandsmitglieder wegen einer Betriebsgemeinschaft weiter gef\u00fchrt werden. Ich glaube, dass wir n\u00e4chstens mit einem Vorschlag werden an Sie herantreten k\u00f6nnen.\\\"\\n\\nSo the letter is confirming receipt of a previous letter and discussing ongoing discussions regarding a business partnership. The title might be something like \\\"Confirmation of Receipt and Update on Business Discussions\\\" but the problem says to extract the title as written in the letter. Wait, the problem says \\\"Title of the letter.\\\" Sometimes letters have a title, but in this case, the letter might not have a specific title. The content starts with the date, then the recipient, then the body.\\n\\nWait, looking at the provided text again, the recipient line is \\\"Herrn Dr. W. Krasting,\\\" followed by the organization name. The organization name might be part of the letter's subject or address. But the letter_title is supposed to be the title. In German letters, sometimes the subject is written in the beginning, but in this case, the example given has a title like \\\"Petition for Environmental Protection\\\". Maybe the letter title here is the subject line. Since the organization name is mentioned, perhaps the title is \\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\".\\n\\nWait, the letter is addressed to Dr. W. Krasting at that exhibition. So the letter's title might be related to the exhibition. Alternatively, maybe the letter title is a specific subject line. However, in this case, the letter is confirming receipt and discussing the exhibition's business. So the title could be \\\"Confirmation of Receipt and Update on Business Discussions Regarding the International Exhibition for Inland Shipping and Hydropower Utilization Basel 1926\\\".\\n\\nBut according to the problem statement, we need to extract the title as it's presented in the letter. If the letter doesn't have an explicit title, then maybe it's based on the context. However, the instructions say to extract the values from the letter. Let's check again.\\n\\nThe user provided the following letter text:\\n\\n\\\"Basel, den 29.M\u00e4rz 1926.\\n\\nT\\n\\nHerrn Dr. W. Krasting,\\n\\nInternationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\n\\nBasel.\\n\\nIch best\u00e4tige Ihnen dankend den Erhalt Ihres Schreibens vom 26. dies und teile Ihnen mit, dass die Besprechungen mit verschiedenen unserer Vorstandsmitglieder wegen einer Betriebsgemeinschaft weiter gef\u00fchrt werden. Ich glaube, dass wir n\u00e4chstens mit einem Vorschlag werden an Sie herantreten k\u00f6nnen.\\n\\nHochachtungsvoll\\\"\\n\\nSo the structure is:\\n\\n- Date: Basel, den 29.M\u00e4rz 1926.\\n\\n- Then a \\\"T\\\", which might be a typo or a section marker.\\n\\n- Recipient: Herrn Dr. W. Krasting,\\n\\n- Organization: Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\n\\n- Location: Basel.\\n\\n- Body of the letter.\\n\\n- Closing: Hochachtungsvoll\\n\\nIn German letters, the \\\"Herrn\\\" is the salutation, and the recipient's name is followed by their position or organization. The organization name might be part of the letter's header. So the letter title might be the organization name. But the problem says \\\"letter_title: Title of the letter.\\\" So perhaps the title is the subject line. However, in this letter, the subject is implied by the content, but there's no explicit title.\\n\\nAlternatively, the letter title could be derived from the context. Since the letter is part of correspondence related to the International Exhibition, perhaps the title is something like \\\"Confirmation of Receipt and Further Discussions on Business Cooperation\\\".\\n\\nBut the problem states to extract the values as they are in the letter. If the letter doesn't have a specific title, perhaps it's empty. However, the example shows a title. Maybe in this case, the title is the organization name.\\n\\nWait, but the problem says \\\"Title of the letter.\\\" If the letter is part of the exhibition's correspondence, perhaps the title is the exhibition's name. However, that's a stretch. The user instructions specify to extract from the letter, not to infer.\\n\\nAlternatively, perhaps the \\\"letter_title\\\" is derived from the body. The body states: \\\"Ich best\u00e4tige Ihnen dankend den Erhalt Ihres Schreibens vom 26. dies und teile Ihnen mit, dass die Besprechungen... weiter gef\u00fchrt werden.\\\" So the main action is confirming receipt and discussing further discussions. The title might be something like \\\"Confirmation of Receipt and Update on Business Discussions\\\".\\n\\nBut without an explicit title, it's hard. However, since the problem requires extracting the values as per the letter, and if the letter doesn't have a title, then it would be \\\"null\\\". Wait, but the example shows a title. The user's instruction says to return \\\"null\\\" only if not included.\\n\\nLet me check the problem statement again: \\\"If a piece of information is not included in the letter, set the value for the corresponding key to 'null'.\\\"\\n\\nSo if the letter doesn't have a title, then letter_title would be \\\"null\\\". However, sometimes letters have a title line. In this case, looking at the provided text, there is no explicit title line. The organization name is in the address line. So perhaps the letter_title is the organization's name as part of the letter's context.\\n\\nBut the problem says to extract from the letter. Maybe the organization's name is considered the title here.\\n\\nAlternatively, the letter_title could be \\\"Confirmation of Receipt and Update on Business Discussions\\\".\\n\\nBut I'm not sure. Let's see similar examples. In the example given by the user, the letter_title is \\\"Petition for Environmental Protection\\\". So it's a specific subject. In this case, the letter is confirming receipt and discussing business, so perhaps the title is \\\"Confirmation of Receipt and Update on Business Discussions Regarding the International Exhibition\\\".\\n\\nBut how to phrase it correctly. However, since the problem says to extract based on the letter, maybe the organization's name is the title.\\n\\nAlternatively, since the letter is part of the International Exhibition, the title might be \\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\".\\n\\nBut wait, the organization name is part of the address, not the title. The letter itself is a response to a previous letter regarding business discussions related to the exhibition.\\n\\nAlternatively, maybe the title is the content of the letter's purpose. Given that the letter is confirming receipt and stating that discussions will continue, the title might be \\\"Confirmation of Receipt and Update on Business Discussions\\\".\\n\\nBut without an explicit title, it's ambiguous. However, the problem expects us to extract based on the letter. Since the user provided the letter's content, which includes the organization name, perhaps that's the title.\\n\\nWait, in the example given, the letter_title is a specific subject. So perhaps for this letter, the title is the purpose of the letter. Let's see: \\\"I confirm to you the receipt of your letter dated the 26th and inform you that the discussions with various members of our board regarding a business partnership will continue. I believe that we will soon present a proposal to you.\\\"\\n\\nSo the title might be \\\"Confirmation of Receipt and Update on Business Discussions\\\".\\n\\nBut the problem requires extracting the values from the letter. Since the letter doesn't have a specific title line, maybe the title is derived from the context. However, the problem states to use the information included in the letter.\\n\\nGiven the ambiguity, but following the instructions, if the letter doesn't have a title line, then letter_title should be \\\"null\\\". However, the problem's example shows a title, so maybe the title is derived from the body.\\n\\nAlternatively, in German correspondence, the title might be included in the letter's header. But looking at the structure:\\n\\nThe date is at the top, then \\\"T\\\" (maybe a typo or section), then the recipient, then the organization name.\\n\\nThe organization name is part of the letter's address, so maybe that's considered the title. For example, in some letters, the organization name is the subject.\\n\\nGiven that, maybe the letter_title is \\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\".\\n\\nBut is that accurate? The letter is about confirming receipt and discussing business related to the exhibition, so the title could be the exhibition name.\\n\\nAlternatively, the title might be \\\"Confirmation of Receipt and Business Discussion Update\\\".\\n\\nBut since the problem requires extracting from the letter, and the organization name is prominently featured, perhaps that's the title.\\n\\nMoving on to sender_persons: The letter is signed \\\"Hochachtungsvoll\\\", but there's no signature or name provided. Therefore, the sender_persons are not mentioned in the letter. Hence, this would be \\\"null\\\".\\n\\nWait, but in the example, the sender_persons is a list of names. If the sender isn't named, then it's null.\\n\\nSimilarly, receiver_persons: \\\"Herrn Dr. W. Krasting\\\", which is the recipient. So receiver_persons is [\\\"Dr. W. Krasting\\\"].\\n\\nsend_date: \\\"Basel, den 29.M\u00e4rz 1926.\\\" So the date is March 29, 1926. Converting to ISO: 1926-03-29.\\n\\nletter_title: As discussed, perhaps the organization name. But the problem says to extract from the letter. If there's no explicit title, but the organization is mentioned, maybe that's it.\\n\\nAlternatively, if the letter's title isn't present, then it's \\\"null\\\". But I think in this case, the organization name might be considered the title.\\n\\nWait, another angle: in the example, the title is \\\"Petition for Environmental Protection\\\", which is a specific subject. Here, the subject is \\\"Confirmation of Receipt and Update on Business Discussions\\\", so the title should reflect that.\\n\\nBut without an explicit title line, how to decide? The problem states to extract from the letter. The letter's body is about confirming receipt and discussing business, so the title would be something like \\\"Confirmation of Receipt and Update on Business Discussions\\\".\\n\\nBut since the problem requires using the information in the letter, perhaps the title is derived from the content. However, the exact wording might be tricky.\\n\\nAlternatively, perhaps the title is not present, so it's \\\"null\\\".\\n\\nThis is a bit ambiguous. Let me check similar historical letters. In many German historical letters from the 1920s, the title or subject might be written in the letter's body. However, in this case, the letter is a formal correspondence addressed to Dr. Krasting. The purpose is to confirm receipt and discuss ongoing discussions. So the title could be \\\"Confirmation of Receipt of Letter and Update on Business Discussions\\\".\\n\\nBut how to phrase it exactly. Given the constraints, perhaps the letter_title is [\\\"Confirmation of Receipt and Update on Business Discussions\\\"].\\n\\nWait, but the example uses a title that's a specific phrase, so this might be acceptable.\\n\\nBut another thought: the problem states \\\"Title of the letter.\\\" In some cases, the title is a phrase that summarizes the letter's content. Since the letter is a confirmation, the title might be \\\"Confirmation of Receipt\\\".\\n\\nAlternatively, given the context of the International Exhibition, perhaps the title is related to that.\\n\\nAlternatively, maybe there's no title, so it's \\\"null\\\". But the example shows a title, so perhaps the system expects the title to be derived.\\n\\nWait, the problem says: \\\"If a piece of information is not included in the letter, set the value for the corresponding key to 'null'.\\\"\\n\\nSo if the letter doesn't have a title line, then letter_title is \\\"null\\\". But in this case, the letter does have the organization's name, which might be considered part of the title.\\n\\nAlternatively, maybe the title is the subject of the correspondence. Since the letter is addressing a previous communication, the title might be \\\"Response to Previous Communication Regarding Business Discussions\\\".\\n\\nBut I'm not sure. Let's see.\\n\\nLooking back at the user's example, the letter_title is \\\"Petition for Environmental Protection\\\", which is a specific subject. So in this case, the letter's title should be something like \\\"Confirmation of Receipt and Update on Business Discussions\\\".\\n\\nGiven that, perhaps the letter_title is [\\\"Confirmation of Receipt and Update on Business Discussions\\\"].\\n\\nAlternatively, in German, the title might be something like \\\"Best\u00e4tigung der Erhaltung Ihres Schreibens und Mitteilung \u00fcber die weiteren Besprechungen\\\", but we need to translate that to English.\\n\\nWait, the instructions don't specify language, but the example is in English. So the title should be in English.\\n\\nGiven that, the letter_title could be \\\"Confirmation of Receipt and Update on Business Discussions\\\".\\n\\nNow, for sender_persons: The letter doesn't mention who wrote it. It's addressed to Dr. Krasting, and the sender is probably someone from the organization, but no name is provided. So sender_persons should be \\\"null\\\".\\n\\nReceiver_persons: The recipient is \\\"Herrn Dr. W. Krasting\\\", so [\\\"Dr. W. Krasting\\\"].\\n\\nsend_date: 1926-03-29.\\n\\nSo putting it all together:\\n\\nletter_title: [\\\"Confirmation of Receipt and Update on Business Discussions\\\"]\\n\\nsender_persons: [\\\"null\\\"] ? Wait, no. The instruction says \\\"If a piece of information is not included in the letter, set the value for the corresponding key to 'null'.\\\"\\n\\nBut the sender_persons are a list, so if not present, it's \\\"null\\\", but since the schema expects a list, the \\\"null\\\" should be a list with one element? Wait, the schema says:\\n\\n\\\"anyOf\\\": [{\\\"items\\\": {\\\"type\\\": \\\"string\\\"}, \\\"type\\\": \\\"array\\\"}, {\\\"type\\\": \\\"null\\\"}]\\n\\nSo for sender_persons, if no info, it's \\\"null\\\", otherwise a list of strings.\\n\\nWait, the example shows:\\n\\n\\\"sender_persons\\\": [\\\"Lisa Simpson\\\"],\\n\\nSo if no info, it's \\\"null\\\".\\n\\nWait, the schema for sender_persons is \\\"anyOf\\\": [array of strings, null].\\n\\nSo if there's no sender, it's \\\"null\\\", which is a single value.\\n\\nTherefore, sender_persons should be \\\"null\\\" if not present.\\n\\nWait, but the problem says: \\\"If a piece of information is not included in the letter, set the value for the corresponding key to 'null'.\\\"\\n\\nSo in this case, since the sender's name isn't mentioned in the letter, sender_persons should be \\\"null\\\".\\n\\nSimilarly, if the title is not present, it's \\\"null\\\", but I think it's present as derived.\\n\\nWait, let me re-examine the letter.\\n\\nThe letter has the following elements:\\n\\n- Date\\n\\n- Recipient\\n\\n- Organization name\\n\\n- Body\\n\\n- Closing\\n\\nThe sender's name isn't listed, so sender_persons is null.\\n\\nThe receiver_persons is \\\"Herrn Dr. W. Krasting\\\", so receiver_persons is [\\\"Dr. W. Krasting\\\"].\\n\\nThe send_date is 1926-03-29.\\n\\nThe letter_title: The problem is whether the organization's name is the title. Since the organization is mentioned in the address, perhaps the title is \\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\".\\n\\nBut that's the name of the exhibition, which is the context of the letter.\\n\\nAlternatively, the title might be the purpose of the letter: confirming receipt and discussing business.\\n\\nGiven that the problem states to extract the title of the letter, which is a bit ambiguous, but in historical context, the title might be the subject of the letter. Given the letter's content, it's a confirmation letter regarding business discussions related to the exhibition.\\n\\nAlternatively, the letter might not have a specific title, so the letter_title is \\\"null\\\".\\n\\nBut in the example provided, the letter_title is present. So perhaps for this case, the title is derived from the context.\\n\\nWait, the problem states: \\\"extract the values of the following keys from the letter\\\".\\n\\nSo if the letter doesn't explicitly state a title, then the letter_title would be \\\"null\\\". But perhaps the organization name serves as the title.\\n\\nWait, but the problem's example shows that the title is a specific phrase related to the content. So in this case, the letter_title should be the phrase that summarizes the letter's content.\\n\\nThe letter says: \\\"Ich best\u00e4tige Ihnen dankend den Erhalt Ihres Schreibens vom 26. dies und teile Ihnen mit, dass die Besprechungen... weiter gef\u00fchrt werden.\\\"\\n\\nTranslation: \\\"I confirm to you, thanking you, the receipt of your letter from the 26th of this month and inform you that the discussions... will continue.\\\"\\n\\nSo the title could be \\\"Confirmation of Receipt of Letter and Update on Business Discussions\\\".\\n\\nBut how to phrase it in the title.\\n\\nGiven that, letter_title should be [\\\"Confirmation of Receipt and Update on Business Discussions\\\"].\\n\\nBut the problem says to extract from the letter, so maybe it's better to take a direct phrase from the letter.\\n\\nThe letter starts with \\\"Ich best\u00e4tige Ihnen dankend...\\\", which is \\\"I confirm to you thank you...\\\", so the title could be \\\"Confirmation of Receipt\\\".\\n\\nBut the example uses a longer title.\\n\\nAlternatively, the letter_title might not be explicitly present, so it's \\\"null\\\". However, given the example, the system expects the title to be derived.\\n\\nThis is a tricky part. Given that, perhaps the correct approach is to infer the title from the context, even if it's not explicitly stated.\\n\\nNow, putting it all together:\\n\\nletter_title: [\\\"Confirmation of Receipt and Update on Business Discussions\\\"]\\n\\nsender_persons: \\\"null\\\" (since no name is given)\\n\\nreceiver_persons: [\\\"Dr. W. Krasting\\\"]\\n\\nsend_date: [\\\"1926-03-29\\\"]\\n\\nWait, but the send_date is a single date, so as a list.\\n\\nThe schema requires each field to be a list, even if single. So send_date is [\\\"1926-03-29\\\"].\\n\\nNow, checking the schema again: the schema specifies that each of the required fields should be a list or null. The schema uses \\\"anyOf\\\": [{\\\"items\\\": {\\\"type\\\": \\\"string\\\"}, \\\"type\\\": \\\"array\\\"}, {\\\"type\\\": \\\"null\\\"}].\\n\\nSo for sender_persons, if no info, it's \\\"null\\\" (a scalar), but the example shows it's a list. Wait, the schema says:\\n\\n\\\"sender_persons\\\": {\\\"anyOf\\\": [{\\\"items\\\": {\\\"type\\\": \\\"string\\\"}, \\\"type\\\": \\\"array\\\"}, {\\\"type\\\": \\\"null\\\"}]}\\n\\nSo it can be an array of strings or null.\\n\\nIn the example, sender_persons is [\\\"Lisa Simpson\\\"], which is an array.\\n\\nIf the information isn't present, it's \\\"null\\\".\\n\\nWait, the schema's description says: \\\"If a piece of information is not included in the letter, set the value for the corresponding key to 'null'.\\\"\\n\\nSo the value should be \\\"null\\\", not an empty array.\\n\\nBut the example shows a non-null value as an array. So the correct approach is:\\n\\n- If the information is present, store it as an array (even if single item).\\n\\n- If not present, store as \\\"null\\\".\\n\\nTherefore, sender_persons is \\\"null\\\", receiver_persons is [\\\"Dr. W. Krasting\\\"], etc.\\n\\nWait, but the problem says \\\"return them in a JSON file where the values corresponding to each key should be stored as a list, even if there is only a single value for a key\\\".\\n\\nBut also says: \\\"If a piece of information is not included in the letter, set the value for the corresponding key to 'null'.\\\"\\n\\nWait, there's a contradiction here. The instructions say to store values as a list, but if not included, set to \\\"null\\\".\\n\\nSo for example, if sender_persons is not present, it's \\\"null\\\", not an empty array.\\n\\nIn the example, sender_persons is an array. But if the letter doesn't mention the sender, it's \\\"null\\\".\\n\\nSo for the current case:\\n\\n- sender_persons: \\\"null\\\" (since no name given)\\n\\n- receiver_persons: [\\\"Dr. W. Krasting\\\"]\\n\\n- send_date: [\\\"1926-03-29\\\"]\\n\\n- letter_title: ??\\n\\nIf the letter doesn't have a title, then letter_title is \\\"null\\\".\\n\\nBut if the organization name is considered the title, then it's an array with that string.\\n\\nThe problem is whether the organization's name is the title.\\n\\nLooking at historical correspondence, often the organization name is part of the letter's header, but the title of the letter would be the subject matter.\\n\\nGiven that, maybe the letter_title is \\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\".\\n\\nBut I'm not certain.\\n\\nAlternatively, since the letter is a confirmation of receipt, the title might be \\\"Confirmation of Receipt\\\".\\n\\nBut without more context, it's hard.\\n\\nWait, in the provided letter, the organization is mentioned in the address line. In German letters, sometimes the recipient's organization is part of the address, and the title might be the subject.\\n\\nBut given that the problem states to extract from the letter, and the letter's content is about confirming receipt and discussing business, the title should be related to that.\\n\\nSo I think the letter_title should be \\\"Confirmation of Receipt and Update on Business Discussions\\\".\\n\\nBut to be precise, let's check the German text:\\n\\n\\\"Ich best\u00e4tige Ihnen dankend den Erhalt Ihres Schreibens vom 26. dies und teile Ihnen mit, dass die Besprechungen mit verschiedenen unserer Vorstandsmitglieder wegen einer Betriebsgemeinschaft weiter gef\u00fchrt werden.\\\"\\n\\nWhich translates to: \\\"I confirm to you, thanking you, the receipt of your letter from the 26th of this month and inform you that the discussions with various members of our board regarding a business partnership will continue.\\\"\\n\\nSo the main action is confirming receipt and stating that discussions continue.\\n\\nThe title could be \\\"Confirmation of Receipt and Update on Business Discussions\\\".\\n\\nBut how to phrase it as a title.\\n\\nAlternatively, the title might be \\\"Response to Previous Letter Regarding Business Discussions\\\".\\n\\nBut the problem says to extract from the letter.\\n\\nGiven all this, I think the safest approach is to set letter_title as the organization name, since that's prominently featured.\\n\\nWait, another angle: in the letter, the line after the recipient is the organization name. In many formal letters, the organization name is part of the address, and the title might be the subject. But without a clear title, perhaps the organization name is the title.\\n\\nAlternatively, if the letter is part of official correspondence for the exhibition, then the title is the exhibition's name.\\n\\nBut given the instructions, if the letter's title isn't explicitly stated, it's \\\"null\\\". However, the organization's name is part of the letter's header, which might be considered the title.\\n\\nThis is really ambiguous, but given that the user example shows a title, and this letter is related to an exhibition, I'll go with:\\n\\nletter_title: [\\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\"]\\n\\nBut I'm not entirely sure.\\n\\nAlternatively, since the letter is addressing the exhibition, the title could be \\\"Business Discussion Update on the International Exhibition\\\".\\n\\nBut without explicit information, it's tricky.\\n\\nGiven the time I've spent, I'll proceed with the following:\\n\\n- send_date: [\\\"1926-03-29\\\"]\\n\\n- receiver_persons: [\\\"Dr. W. Krasting\\\"]\\n\\n- sender_persons: \\\"null\\\" (as the letter doesn't mention the sender's name)\\n\\n- letter_title: \\\"null\\\" (since no explicit title is present)\\n\\nBut wait, the organization name is part of the letter. Maybe the title is the exhibition name.\\n\\nAlternatively, since the letter is part of the exhibition's correspondence, the title might be the exhibition's name.\\n\\nIn historical context, the exhibition's name would be the subject of the letter, so it's reasonable to set the letter_title as the exhibition name.\\n\\nThus:\\n\\nletter_title: [\\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\"]\\n\\nBut the example shows a title like \\\"Petition for Environmental Protection\\\", which is specific to the content. Here, the content is about business discussions related to the exhibition, so perhaps the title should reflect that.\\n\\nGiven the uncertainty, but following the structure, I think the best approach is to set letter_title as the exhibition name, as it's the primary context.\\n\\nSo final values:\\n\\nletter_title: [\\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\"]\\n\\nsender_persons: \\\"null\\\"\\n\\nreceiver_persons: [\\\"Dr. W. Krasting\\\"]\\n\\nsend_date: [\\\"1926-03-29\\\"]\\n\\nBut wait, the schema requires \\\"send_date\\\" to be a list. The example shows [\\\"1993-03-12\\\"], so yes.\\n\\nNow, checking the required fields: \\\"send_date\\\", \\\"letter_title\\\", \\\"sender_persons\\\", \\\"receiver_persons\\\" must all be present.\\n\\nIn the JSON, they are all included.\\n\\nNow, formatting to the JSON schema provided.\\n\\nThe schema has:\\n\\n{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": ...,\\n \\\"receiver_persons\\\": ...,\\n \\\"send_date\\\": ...,\\n \\\"sender_persons\\\": ...\\n }\\n}\\n\\nSo the final JSON should have \\\"metadata\\\" as the key.\\n\\nWait, the schema says:\\n\\n{\\n \\\"metadata\\\": {\\n \\\"$ref\\\": \\\"#/$defs/Metadata\\\"\\n }\\n}\\n\\nAnd the Metadata object includes the four required fields.\\n\\nSo the final JSON should be:\\n\\n{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [\\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\"],\\n \\\"receiver_persons\\\": [\\\"Dr. W. Krasting\\\"],\\n \\\"send_date\\\": [\\\"1926-03-29\\\"],\\n \\\"sender_persons\\\": null\\n }\\n}\\n\\nBut wait, the schema says sender_persons can be a list or null. But in the example, it's a list. However, according to the problem's instruction, if info is not included, it's \\\"null\\\".\\n\\nBut the schema allows \\\"null\\\" as a value. So sender_persons should be null (not a list).\\n\\nWait, the schema's definition for sender_persons is:\\n\\n\\\"sender_persons\\\": {\\\"anyOf\\\": [{\\\"items\\\": {\\\"type\\\": \\\"string\\\"}, \\\"type\\\": \\\"array\\\"}, {\\\"type\\\": \\\"null\\\"}]}\\n\\nSo it's either an array or null.\\n\\nTherefore, if no sender is mentioned, it's \\\"null\\\", not an empty array.\\n\\nIn the JSON, it's a scalar value, not a list.\\n\\nSo the correct representation would be:\\n\\n\\\"sender_persons\\\": null\\n\\nSimilarly, letter_title is an array if present.\\n\\nSo the final JSON should be:\\n\\n{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [\\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\"],\\n \\\"receiver_persons\\\": [\\\"Dr. W. Krasting\\\"],\\n \\\"send_date\\\": [\\\"1926-03-29\\\"],\\n \\\"sender_persons\\\": null\\n }\\n}\\n\\nBut wait, the example shows sender_persons as a list. However, according to the schema, it's acceptable to be null.\\n\\nYes, because the schema allows for \\\"anyOf\\\" [array, null].\\n\\nSo this should be correct.\\n\\nAnother check: the example's sender_persons is [\\\"Lisa Simpson\\\"], but if the letter doesn't have a sender, it's null.\\n\\nTherefore, the final JSON should have sender_persons as null.\\n\\nNow, the question is whether the letter_title is the exhibition name or something else.\\n\\nAlternatively, if the letter has no explicit title, then it should be null.\\n\\nBut given the context, the exhibition name is the main context, so it's reasonable to include it.\\n\\nAlternatively, the title could be \\\"Confirmation of Receipt and Update on Business Discussions\\\".\\n\\nBut how to determine.\\n\\nGiven the time I've spent, I think the safest approach is to set letter_title to the exhibition name, since it's prominently featured and the context of the letter.\\n\\nSo final answer:\\n\\n{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [\\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\"],\\n \\\"receiver_persons\\\": [\\\"Dr. W. Krasting\\\"],\\n \\\"send_date\\\": [\\\"1926-03-29\\\"],\\n \\\"sender_persons\\\": null\\n }\\n}\\n\\nWait, but the letter_title is in German. The example uses English, but the problem doesn't specify language. The instructions say \\\"extract the values\\\", so if the letter has German text, the title should be in German.\\n\\nThe schema doesn't specify language, so it's acceptable to have the title in German.\\n\\nYes, the user's example had an English title, but the actual letter's title is in German.\\n\\nTherefore, the letter_title should be [\\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\"].\\n\\nThus, the JSON should include that.\\n\",\"reasoning_details\":[{\"format\":\"unknown\",\"index\":0,\"type\":\"reasoning.text\",\"text\":\"Okay, let's tackle this problem step by step. So, I need to extract specific information from a historical letter and format it into a JSON according to the given schema. Let me start by understanding what exactly is required.\\n\\nFirst, the user provided a JSON schema that defines the structure of the output. The main object should have a \\\"metadata\\\" key, which is an object containing four required fields: letter_title, sender_persons, send_date, and receiver_persons. Each of these fields should be a list, even if there's only one value. If a field isn't present in the letter, it should be \\\"null\\\". The date must be in ISO format (YYYY-MM-DD), and the sender/receiver names should be in arrays.\\n\\nNow, looking at the letter image description. The user mentioned it's a historical letter from 1926, so I need to parse the details from the provided text. Wait, the actual image content isn't here; instead, there's a text description of the letter. Let me check the example given in the problem statement.\\n\\nThe example shows a JSON with example values. But the user provided a specific letter description here. Let me read the letter details again.\\n\\nThe letter starts with \\\"Basel, den 29.M\u00e4rz 1926.\\\" So the date is 29th March 1926. Need to convert that to ISO format. March is the 3rd month, so 1926-03-29.\\n\\nNext, the sender_persons. The letter is addressed to \\\"Herrn Dr. W. Krasting,\\\" and the sender seems to be someone at the \\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926.\\\" But wait, the sender's name isn't explicitly stated here. Wait, in the letter, the salutation is \\\"Herrn Dr. W. Krasting,\\\" which is the recipient. The sender's name isn't directly written out. However, the text mentions \\\"Ich best\u00e4tige Ihnen dankend den Erhalt Ihres Schreibens vom 26. dies...\\\" so the sender is probably someone from the organization mentioned. But the problem says to extract the sender_persons from the letter.\\n\\nWait, in the letter, the closing is \\\"Hochachtungsvoll,\\\" which is a common closing for formal letters, but the sender's name isn't listed. Wait, maybe there's a mistake here. Let me check again.\\n\\nLooking at the provided text:\\n\\n\\\"Basel, den 29.M\u00e4rz 1926.\\n\\nT\\n\\nHerrn Dr. W. Krasting,\\n\\nInternationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\n\\nBasel.\\n\\nIch best\u00e4tige Ihnen dankend den Erhalt Ihres Schreibens vom 26. dies und teile Ihnen mit, dass die Besprechungen mit verschiedenen unserer Vorstandsmitglieder wegen einer Betriebsgemeinschaft weiter gef\u00fchrt werden. Ich glaube, dass wir n\u00e4chstens mit einem Vorschlag werden an Sie herantreten k\u00f6nnen.\\n\\nHochachtungsvoll\\\"\\n\\nWait, the sender's name isn't present in the visible text. The letter is addressed to Herr Dr. W. Krasting, and the sender might be implied to be a representative of the International Exhibition. But the problem states to extract the sender_persons from the letter. Since the sender's name isn't explicitly mentioned here, maybe it's \\\"null\\\"?\\n\\nBut wait, the example shows sender_persons as [\\\"Lisa Simpson\\\"], so maybe in some cases the sender is known. Let me check the content again.\\n\\nThe letter says \\\"Ich best\u00e4tige Ihnen...\\\", which translates to \\\"I confirm to you...\\\" So the sender is the person writing the letter. However, the sender's name isn't written out in the letter. The only mention is the organization name: \\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\". But the problem says to extract the person's name(s). If the sender's name isn't written, then it would be \\\"null\\\". But maybe the organization's name is considered the sender? But the instructions specify \\\"Name(s) of the person(s)\\\", so perhaps it's not the organization.\\n\\nWait, in formal letters, sometimes the sender's name isn't written but is part of the organization. But according to the problem statement, the sender_persons should be the person(s) who wrote the letter. If the letter is from the organization, maybe the sender_persons are the organization's representatives, but since we don't have individual names, perhaps it's \\\"null\\\".\\n\\nWait, but the problem says \\\"If a piece of information is not included in the letter, set the value for the corresponding key to 'null'.\\\"\\n\\nSo if the sender's name is not present, it's \\\"null\\\".\\n\\nSimilarly, receiver_persons is \\\"Herrn Dr. W. Krasting\\\", which would be [\\\"Dr. W. Krasting\\\"].\\n\\nLetter title: The title might be the subject line or the main topic. The letter mentions \\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\", which is the name of the exhibition. So perhaps the letter title is related to that.\\n\\nBut the example shows a title like \\\"Petition for Environmental Protection\\\". So the letter_title would be the main subject. Let me check the content.\\n\\nThe letter says: \\\"Ich best\u00e4tige Ihnen dankend den Erhalt Ihres Schreibens vom 26. dies und teile Ihnen mit, dass die Besprechungen mit verschiedenen unserer Vorstandsmitglieder wegen einer Betriebsgemeinschaft weiter gef\u00fchrt werden. Ich glaube, dass wir n\u00e4chstens mit einem Vorschlag werden an Sie herantreten k\u00f6nnen.\\\"\\n\\nSo the letter is confirming receipt of a previous letter and discussing ongoing discussions regarding a business partnership. The title might be something like \\\"Confirmation of Receipt and Update on Business Discussions\\\" but the problem says to extract the title as written in the letter. Wait, the problem says \\\"Title of the letter.\\\" Sometimes letters have a title, but in this case, the letter might not have a specific title. The content starts with the date, then the recipient, then the body.\\n\\nWait, looking at the provided text again, the recipient line is \\\"Herrn Dr. W. Krasting,\\\" followed by the organization name. The organization name might be part of the letter's subject or address. But the letter_title is supposed to be the title. In German letters, sometimes the subject is written in the beginning, but in this case, the example given has a title like \\\"Petition for Environmental Protection\\\". Maybe the letter title here is the subject line. Since the organization name is mentioned, perhaps the title is \\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\".\\n\\nWait, the letter is addressed to Dr. W. Krasting at that exhibition. So the letter's title might be related to the exhibition. Alternatively, maybe the letter title is a specific subject line. However, in this case, the letter is confirming receipt and discussing the exhibition's business. So the title could be \\\"Confirmation of Receipt and Update on Business Discussions Regarding the International Exhibition for Inland Shipping and Hydropower Utilization Basel 1926\\\".\\n\\nBut according to the problem statement, we need to extract the title as it's presented in the letter. If the letter doesn't have an explicit title, then maybe it's based on the context. However, the instructions say to extract the values from the letter. Let's check again.\\n\\nThe user provided the following letter text:\\n\\n\\\"Basel, den 29.M\u00e4rz 1926.\\n\\nT\\n\\nHerrn Dr. W. Krasting,\\n\\nInternationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\n\\nBasel.\\n\\nIch best\u00e4tige Ihnen dankend den Erhalt Ihres Schreibens vom 26. dies und teile Ihnen mit, dass die Besprechungen mit verschiedenen unserer Vorstandsmitglieder wegen einer Betriebsgemeinschaft weiter gef\u00fchrt werden. Ich glaube, dass wir n\u00e4chstens mit einem Vorschlag werden an Sie herantreten k\u00f6nnen.\\n\\nHochachtungsvoll\\\"\\n\\nSo the structure is:\\n\\n- Date: Basel, den 29.M\u00e4rz 1926.\\n\\n- Then a \\\"T\\\", which might be a typo or a section marker.\\n\\n- Recipient: Herrn Dr. W. Krasting,\\n\\n- Organization: Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\n\\n- Location: Basel.\\n\\n- Body of the letter.\\n\\n- Closing: Hochachtungsvoll\\n\\nIn German letters, the \\\"Herrn\\\" is the salutation, and the recipient's name is followed by their position or organization. The organization name might be part of the letter's header. So the letter title might be the organization name. But the problem says \\\"letter_title: Title of the letter.\\\" So perhaps the title is the subject line. However, in this letter, the subject is implied by the content, but there's no explicit title.\\n\\nAlternatively, the letter title could be derived from the context. Since the letter is part of correspondence related to the International Exhibition, perhaps the title is something like \\\"Confirmation of Receipt and Further Discussions on Business Cooperation\\\".\\n\\nBut the problem states to extract the values as they are in the letter. If the letter doesn't have a specific title, perhaps it's empty. However, the example shows a title. Maybe in this case, the title is the organization name.\\n\\nWait, but the problem says \\\"Title of the letter.\\\" If the letter is part of the exhibition's correspondence, perhaps the title is the exhibition's name. However, that's a stretch. The user instructions specify to extract from the letter, not to infer.\\n\\nAlternatively, perhaps the \\\"letter_title\\\" is derived from the body. The body states: \\\"Ich best\u00e4tige Ihnen dankend den Erhalt Ihres Schreibens vom 26. dies und teile Ihnen mit, dass die Besprechungen... weiter gef\u00fchrt werden.\\\" So the main action is confirming receipt and discussing further discussions. The title might be something like \\\"Confirmation of Receipt and Update on Business Discussions\\\".\\n\\nBut without an explicit title, it's hard. However, since the problem requires extracting the values as per the letter, and if the letter doesn't have a title, then it would be \\\"null\\\". Wait, but the example shows a title. The user's instruction says to return \\\"null\\\" only if not included.\\n\\nLet me check the problem statement again: \\\"If a piece of information is not included in the letter, set the value for the corresponding key to 'null'.\\\"\\n\\nSo if the letter doesn't have a title, then letter_title would be \\\"null\\\". However, sometimes letters have a title line. In this case, looking at the provided text, there is no explicit title line. The organization name is in the address line. So perhaps the letter_title is the organization's name as part of the letter's context.\\n\\nBut the problem says to extract from the letter. Maybe the organization's name is considered the title here.\\n\\nAlternatively, the letter_title could be \\\"Confirmation of Receipt and Update on Business Discussions\\\".\\n\\nBut I'm not sure. Let's see similar examples. In the example given by the user, the letter_title is \\\"Petition for Environmental Protection\\\". So it's a specific subject. In this case, the letter is confirming receipt and discussing business, so perhaps the title is \\\"Confirmation of Receipt and Update on Business Discussions Regarding the International Exhibition\\\".\\n\\nBut how to phrase it correctly. However, since the problem says to extract based on the letter, maybe the organization's name is the title.\\n\\nAlternatively, since the letter is part of the International Exhibition, the title might be \\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\".\\n\\nBut wait, the organization name is part of the address, not the title. The letter itself is a response to a previous letter regarding business discussions related to the exhibition.\\n\\nAlternatively, maybe the title is the content of the letter's purpose. Given that the letter is confirming receipt and stating that discussions will continue, the title might be \\\"Confirmation of Receipt and Update on Business Discussions\\\".\\n\\nBut without an explicit title, it's ambiguous. However, the problem expects us to extract based on the letter. Since the user provided the letter's content, which includes the organization name, perhaps that's the title.\\n\\nWait, in the example given, the letter_title is a specific subject. So perhaps for this letter, the title is the purpose of the letter. Let's see: \\\"I confirm to you the receipt of your letter dated the 26th and inform you that the discussions with various members of our board regarding a business partnership will continue. I believe that we will soon present a proposal to you.\\\"\\n\\nSo the title might be \\\"Confirmation of Receipt and Update on Business Discussions\\\".\\n\\nBut the problem requires extracting the values from the letter. Since the letter doesn't have a specific title line, maybe the title is derived from the context. However, the problem states to use the information included in the letter.\\n\\nGiven the ambiguity, but following the instructions, if the letter doesn't have a title line, then letter_title should be \\\"null\\\". However, the problem's example shows a title, so maybe the title is derived from the body.\\n\\nAlternatively, in German correspondence, the title might be included in the letter's header. But looking at the structure:\\n\\nThe date is at the top, then \\\"T\\\" (maybe a typo or section), then the recipient, then the organization name.\\n\\nThe organization name is part of the letter's address, so maybe that's considered the title. For example, in some letters, the organization name is the subject.\\n\\nGiven that, maybe the letter_title is \\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\".\\n\\nBut is that accurate? The letter is about confirming receipt and discussing business related to the exhibition, so the title could be the exhibition name.\\n\\nAlternatively, the title might be \\\"Confirmation of Receipt and Business Discussion Update\\\".\\n\\nBut since the problem requires extracting from the letter, and the organization name is prominently featured, perhaps that's the title.\\n\\nMoving on to sender_persons: The letter is signed \\\"Hochachtungsvoll\\\", but there's no signature or name provided. Therefore, the sender_persons are not mentioned in the letter. Hence, this would be \\\"null\\\".\\n\\nWait, but in the example, the sender_persons is a list of names. If the sender isn't named, then it's null.\\n\\nSimilarly, receiver_persons: \\\"Herrn Dr. W. Krasting\\\", which is the recipient. So receiver_persons is [\\\"Dr. W. Krasting\\\"].\\n\\nsend_date: \\\"Basel, den 29.M\u00e4rz 1926.\\\" So the date is March 29, 1926. Converting to ISO: 1926-03-29.\\n\\nletter_title: As discussed, perhaps the organization name. But the problem says to extract from the letter. If there's no explicit title, but the organization is mentioned, maybe that's it.\\n\\nAlternatively, if the letter's title isn't present, then it's \\\"null\\\". But I think in this case, the organization name might be considered the title.\\n\\nWait, another angle: in the example, the title is \\\"Petition for Environmental Protection\\\", which is a specific subject. Here, the subject is \\\"Confirmation of Receipt and Update on Business Discussions\\\", so the title should reflect that.\\n\\nBut without an explicit title line, how to decide? The problem states to extract from the letter. The letter's body is about confirming receipt and discussing business, so the title would be something like \\\"Confirmation of Receipt and Update on Business Discussions\\\".\\n\\nBut since the problem requires using the information in the letter, perhaps the title is derived from the content. However, the exact wording might be tricky.\\n\\nAlternatively, perhaps the title is not present, so it's \\\"null\\\".\\n\\nThis is a bit ambiguous. Let me check similar historical letters. In many German historical letters from the 1920s, the title or subject might be written in the letter's body. However, in this case, the letter is a formal correspondence addressed to Dr. Krasting. The purpose is to confirm receipt and discuss ongoing discussions. So the title could be \\\"Confirmation of Receipt of Letter and Update on Business Discussions\\\".\\n\\nBut how to phrase it exactly. Given the constraints, perhaps the letter_title is [\\\"Confirmation of Receipt and Update on Business Discussions\\\"].\\n\\nWait, but the example uses a title that's a specific phrase, so this might be acceptable.\\n\\nBut another thought: the problem states \\\"Title of the letter.\\\" In some cases, the title is a phrase that summarizes the letter's content. Since the letter is a confirmation, the title might be \\\"Confirmation of Receipt\\\".\\n\\nAlternatively, given the context of the International Exhibition, perhaps the title is related to that.\\n\\nAlternatively, maybe there's no title, so it's \\\"null\\\". But the example shows a title, so perhaps the system expects the title to be derived.\\n\\nWait, the problem says: \\\"If a piece of information is not included in the letter, set the value for the corresponding key to 'null'.\\\"\\n\\nSo if the letter doesn't have a title line, then letter_title is \\\"null\\\". But in this case, the letter does have the organization's name, which might be considered part of the title.\\n\\nAlternatively, maybe the title is the subject of the correspondence. Since the letter is addressing a previous communication, the title might be \\\"Response to Previous Communication Regarding Business Discussions\\\".\\n\\nBut I'm not sure. Let's see.\\n\\nLooking back at the user's example, the letter_title is \\\"Petition for Environmental Protection\\\", which is a specific subject. So in this case, the letter's title should be something like \\\"Confirmation of Receipt and Update on Business Discussions\\\".\\n\\nGiven that, perhaps the letter_title is [\\\"Confirmation of Receipt and Update on Business Discussions\\\"].\\n\\nAlternatively, in German, the title might be something like \\\"Best\u00e4tigung der Erhaltung Ihres Schreibens und Mitteilung \u00fcber die weiteren Besprechungen\\\", but we need to translate that to English.\\n\\nWait, the instructions don't specify language, but the example is in English. So the title should be in English.\\n\\nGiven that, the letter_title could be \\\"Confirmation of Receipt and Update on Business Discussions\\\".\\n\\nNow, for sender_persons: The letter doesn't mention who wrote it. It's addressed to Dr. Krasting, and the sender is probably someone from the organization, but no name is provided. So sender_persons should be \\\"null\\\".\\n\\nReceiver_persons: The recipient is \\\"Herrn Dr. W. Krasting\\\", so [\\\"Dr. W. Krasting\\\"].\\n\\nsend_date: 1926-03-29.\\n\\nSo putting it all together:\\n\\nletter_title: [\\\"Confirmation of Receipt and Update on Business Discussions\\\"]\\n\\nsender_persons: [\\\"null\\\"] ? Wait, no. The instruction says \\\"If a piece of information is not included in the letter, set the value for the corresponding key to 'null'.\\\"\\n\\nBut the sender_persons are a list, so if not present, it's \\\"null\\\", but since the schema expects a list, the \\\"null\\\" should be a list with one element? Wait, the schema says:\\n\\n\\\"anyOf\\\": [{\\\"items\\\": {\\\"type\\\": \\\"string\\\"}, \\\"type\\\": \\\"array\\\"}, {\\\"type\\\": \\\"null\\\"}]\\n\\nSo for sender_persons, if no info, it's \\\"null\\\", otherwise a list of strings.\\n\\nWait, the example shows:\\n\\n\\\"sender_persons\\\": [\\\"Lisa Simpson\\\"],\\n\\nSo if no info, it's \\\"null\\\".\\n\\nWait, the schema for sender_persons is \\\"anyOf\\\": [array of strings, null].\\n\\nSo if there's no sender, it's \\\"null\\\", which is a single value.\\n\\nTherefore, sender_persons should be \\\"null\\\" if not present.\\n\\nWait, but the problem says: \\\"If a piece of information is not included in the letter, set the value for the corresponding key to 'null'.\\\"\\n\\nSo in this case, since the sender's name isn't mentioned in the letter, sender_persons should be \\\"null\\\".\\n\\nSimilarly, if the title is not present, it's \\\"null\\\", but I think it's present as derived.\\n\\nWait, let me re-examine the letter.\\n\\nThe letter has the following elements:\\n\\n- Date\\n\\n- Recipient\\n\\n- Organization name\\n\\n- Body\\n\\n- Closing\\n\\nThe sender's name isn't listed, so sender_persons is null.\\n\\nThe receiver_persons is \\\"Herrn Dr. W. Krasting\\\", so receiver_persons is [\\\"Dr. W. Krasting\\\"].\\n\\nThe send_date is 1926-03-29.\\n\\nThe letter_title: The problem is whether the organization's name is the title. Since the organization is mentioned in the address, perhaps the title is \\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\".\\n\\nBut that's the name of the exhibition, which is the context of the letter.\\n\\nAlternatively, the title might be the purpose of the letter: confirming receipt and discussing business.\\n\\nGiven that the problem states to extract the title of the letter, which is a bit ambiguous, but in historical context, the title might be the subject of the letter. Given the letter's content, it's a confirmation letter regarding business discussions related to the exhibition.\\n\\nAlternatively, the letter might not have a specific title, so the letter_title is \\\"null\\\".\\n\\nBut in the example provided, the letter_title is present. So perhaps for this case, the title is derived from the context.\\n\\nWait, the problem states: \\\"extract the values of the following keys from the letter\\\".\\n\\nSo if the letter doesn't explicitly state a title, then the letter_title would be \\\"null\\\". But perhaps the organization name serves as the title.\\n\\nWait, but the problem's example shows that the title is a specific phrase related to the content. So in this case, the letter_title should be the phrase that summarizes the letter's content.\\n\\nThe letter says: \\\"Ich best\u00e4tige Ihnen dankend den Erhalt Ihres Schreibens vom 26. dies und teile Ihnen mit, dass die Besprechungen... weiter gef\u00fchrt werden.\\\"\\n\\nTranslation: \\\"I confirm to you, thanking you, the receipt of your letter from the 26th of this month and inform you that the discussions... will continue.\\\"\\n\\nSo the title could be \\\"Confirmation of Receipt of Letter and Update on Business Discussions\\\".\\n\\nBut how to phrase it in the title.\\n\\nGiven that, letter_title should be [\\\"Confirmation of Receipt and Update on Business Discussions\\\"].\\n\\nBut the problem says to extract from the letter, so maybe it's better to take a direct phrase from the letter.\\n\\nThe letter starts with \\\"Ich best\u00e4tige Ihnen dankend...\\\", which is \\\"I confirm to you thank you...\\\", so the title could be \\\"Confirmation of Receipt\\\".\\n\\nBut the example uses a longer title.\\n\\nAlternatively, the letter_title might not be explicitly present, so it's \\\"null\\\". However, given the example, the system expects the title to be derived.\\n\\nThis is a tricky part. Given that, perhaps the correct approach is to infer the title from the context, even if it's not explicitly stated.\\n\\nNow, putting it all together:\\n\\nletter_title: [\\\"Confirmation of Receipt and Update on Business Discussions\\\"]\\n\\nsender_persons: \\\"null\\\" (since no name is given)\\n\\nreceiver_persons: [\\\"Dr. W. Krasting\\\"]\\n\\nsend_date: [\\\"1926-03-29\\\"]\\n\\nWait, but the send_date is a single date, so as a list.\\n\\nThe schema requires each field to be a list, even if single. So send_date is [\\\"1926-03-29\\\"].\\n\\nNow, checking the schema again: the schema specifies that each of the required fields should be a list or null. The schema uses \\\"anyOf\\\": [{\\\"items\\\": {\\\"type\\\": \\\"string\\\"}, \\\"type\\\": \\\"array\\\"}, {\\\"type\\\": \\\"null\\\"}].\\n\\nSo for sender_persons, if no info, it's \\\"null\\\" (a scalar), but the example shows it's a list. Wait, the schema says:\\n\\n\\\"sender_persons\\\": {\\\"anyOf\\\": [{\\\"items\\\": {\\\"type\\\": \\\"string\\\"}, \\\"type\\\": \\\"array\\\"}, {\\\"type\\\": \\\"null\\\"}]}\\n\\nSo it can be an array of strings or null.\\n\\nIn the example, sender_persons is [\\\"Lisa Simpson\\\"], which is an array.\\n\\nIf the information isn't present, it's \\\"null\\\".\\n\\nWait, the schema's description says: \\\"If a piece of information is not included in the letter, set the value for the corresponding key to 'null'.\\\"\\n\\nSo the value should be \\\"null\\\", not an empty array.\\n\\nBut the example shows a non-null value as an array. So the correct approach is:\\n\\n- If the information is present, store it as an array (even if single item).\\n\\n- If not present, store as \\\"null\\\".\\n\\nTherefore, sender_persons is \\\"null\\\", receiver_persons is [\\\"Dr. W. Krasting\\\"], etc.\\n\\nWait, but the problem says \\\"return them in a JSON file where the values corresponding to each key should be stored as a list, even if there is only a single value for a key\\\".\\n\\nBut also says: \\\"If a piece of information is not included in the letter, set the value for the corresponding key to 'null'.\\\"\\n\\nWait, there's a contradiction here. The instructions say to store values as a list, but if not included, set to \\\"null\\\".\\n\\nSo for example, if sender_persons is not present, it's \\\"null\\\", not an empty array.\\n\\nIn the example, sender_persons is an array. But if the letter doesn't mention the sender, it's \\\"null\\\".\\n\\nSo for the current case:\\n\\n- sender_persons: \\\"null\\\" (since no name given)\\n\\n- receiver_persons: [\\\"Dr. W. Krasting\\\"]\\n\\n- send_date: [\\\"1926-03-29\\\"]\\n\\n- letter_title: ??\\n\\nIf the letter doesn't have a title, then letter_title is \\\"null\\\".\\n\\nBut if the organization name is considered the title, then it's an array with that string.\\n\\nThe problem is whether the organization's name is the title.\\n\\nLooking at historical correspondence, often the organization name is part of the letter's header, but the title of the letter would be the subject matter.\\n\\nGiven that, maybe the letter_title is \\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\".\\n\\nBut I'm not certain.\\n\\nAlternatively, since the letter is a confirmation of receipt, the title might be \\\"Confirmation of Receipt\\\".\\n\\nBut without more context, it's hard.\\n\\nWait, in the provided letter, the organization is mentioned in the address line. In German letters, sometimes the recipient's organization is part of the address, and the title might be the subject.\\n\\nBut given that the problem states to extract from the letter, and the letter's content is about confirming receipt and discussing business, the title should be related to that.\\n\\nSo I think the letter_title should be \\\"Confirmation of Receipt and Update on Business Discussions\\\".\\n\\nBut to be precise, let's check the German text:\\n\\n\\\"Ich best\u00e4tige Ihnen dankend den Erhalt Ihres Schreibens vom 26. dies und teile Ihnen mit, dass die Besprechungen mit verschiedenen unserer Vorstandsmitglieder wegen einer Betriebsgemeinschaft weiter gef\u00fchrt werden.\\\"\\n\\nWhich translates to: \\\"I confirm to you, thanking you, the receipt of your letter from the 26th of this month and inform you that the discussions with various members of our board regarding a business partnership will continue.\\\"\\n\\nSo the main action is confirming receipt and stating that discussions continue.\\n\\nThe title could be \\\"Confirmation of Receipt and Update on Business Discussions\\\".\\n\\nBut how to phrase it as a title.\\n\\nAlternatively, the title might be \\\"Response to Previous Letter Regarding Business Discussions\\\".\\n\\nBut the problem says to extract from the letter.\\n\\nGiven all this, I think the safest approach is to set letter_title as the organization name, since that's prominently featured.\\n\\nWait, another angle: in the letter, the line after the recipient is the organization name. In many formal letters, the organization name is part of the address, and the title might be the subject. But without a clear title, perhaps the organization name is the title.\\n\\nAlternatively, if the letter is part of official correspondence for the exhibition, then the title is the exhibition's name.\\n\\nBut given the instructions, if the letter's title isn't explicitly stated, it's \\\"null\\\". However, the organization's name is part of the letter's header, which might be considered the title.\\n\\nThis is really ambiguous, but given that the user example shows a title, and this letter is related to an exhibition, I'll go with:\\n\\nletter_title: [\\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\"]\\n\\nBut I'm not entirely sure.\\n\\nAlternatively, since the letter is addressing the exhibition, the title could be \\\"Business Discussion Update on the International Exhibition\\\".\\n\\nBut without explicit information, it's tricky.\\n\\nGiven the time I've spent, I'll proceed with the following:\\n\\n- send_date: [\\\"1926-03-29\\\"]\\n\\n- receiver_persons: [\\\"Dr. W. Krasting\\\"]\\n\\n- sender_persons: \\\"null\\\" (as the letter doesn't mention the sender's name)\\n\\n- letter_title: \\\"null\\\" (since no explicit title is present)\\n\\nBut wait, the organization name is part of the letter. Maybe the title is the exhibition name.\\n\\nAlternatively, since the letter is part of the exhibition's correspondence, the title might be the exhibition's name.\\n\\nIn historical context, the exhibition's name would be the subject of the letter, so it's reasonable to set the letter_title as the exhibition name.\\n\\nThus:\\n\\nletter_title: [\\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\"]\\n\\nBut the example shows a title like \\\"Petition for Environmental Protection\\\", which is specific to the content. Here, the content is about business discussions related to the exhibition, so perhaps the title should reflect that.\\n\\nGiven the uncertainty, but following the structure, I think the best approach is to set letter_title as the exhibition name, as it's the primary context.\\n\\nSo final values:\\n\\nletter_title: [\\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\"]\\n\\nsender_persons: \\\"null\\\"\\n\\nreceiver_persons: [\\\"Dr. W. Krasting\\\"]\\n\\nsend_date: [\\\"1926-03-29\\\"]\\n\\nBut wait, the schema requires \\\"send_date\\\" to be a list. The example shows [\\\"1993-03-12\\\"], so yes.\\n\\nNow, checking the required fields: \\\"send_date\\\", \\\"letter_title\\\", \\\"sender_persons\\\", \\\"receiver_persons\\\" must all be present.\\n\\nIn the JSON, they are all included.\\n\\nNow, formatting to the JSON schema provided.\\n\\nThe schema has:\\n\\n{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": ...,\\n \\\"receiver_persons\\\": ...,\\n \\\"send_date\\\": ...,\\n \\\"sender_persons\\\": ...\\n }\\n}\\n\\nSo the final JSON should have \\\"metadata\\\" as the key.\\n\\nWait, the schema says:\\n\\n{\\n \\\"metadata\\\": {\\n \\\"$ref\\\": \\\"#/$defs/Metadata\\\"\\n }\\n}\\n\\nAnd the Metadata object includes the four required fields.\\n\\nSo the final JSON should be:\\n\\n{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [\\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\"],\\n \\\"receiver_persons\\\": [\\\"Dr. W. Krasting\\\"],\\n \\\"send_date\\\": [\\\"1926-03-29\\\"],\\n \\\"sender_persons\\\": null\\n }\\n}\\n\\nBut wait, the schema says sender_persons can be a list or null. But in the example, it's a list. However, according to the problem's instruction, if info is not included, it's \\\"null\\\".\\n\\nBut the schema allows \\\"null\\\" as a value. So sender_persons should be null (not a list).\\n\\nWait, the schema's definition for sender_persons is:\\n\\n\\\"sender_persons\\\": {\\\"anyOf\\\": [{\\\"items\\\": {\\\"type\\\": \\\"string\\\"}, \\\"type\\\": \\\"array\\\"}, {\\\"type\\\": \\\"null\\\"}]}\\n\\nSo it's either an array or null.\\n\\nTherefore, if no sender is mentioned, it's \\\"null\\\", not an empty array.\\n\\nIn the JSON, it's a scalar value, not a list.\\n\\nSo the correct representation would be:\\n\\n\\\"sender_persons\\\": null\\n\\nSimilarly, letter_title is an array if present.\\n\\nSo the final JSON should be:\\n\\n{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [\\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\"],\\n \\\"receiver_persons\\\": [\\\"Dr. W. Krasting\\\"],\\n \\\"send_date\\\": [\\\"1926-03-29\\\"],\\n \\\"sender_persons\\\": null\\n }\\n}\\n\\nBut wait, the example shows sender_persons as a list. However, according to the schema, it's acceptable to be null.\\n\\nYes, because the schema allows for \\\"anyOf\\\" [array, null].\\n\\nSo this should be correct.\\n\\nAnother check: the example's sender_persons is [\\\"Lisa Simpson\\\"], but if the letter doesn't have a sender, it's null.\\n\\nTherefore, the final JSON should have sender_persons as null.\\n\\nNow, the question is whether the letter_title is the exhibition name or something else.\\n\\nAlternatively, if the letter has no explicit title, then it should be null.\\n\\nBut given the context, the exhibition name is the main context, so it's reasonable to include it.\\n\\nAlternatively, the title could be \\\"Confirmation of Receipt and Update on Business Discussions\\\".\\n\\nBut how to determine.\\n\\nGiven the time I've spent, I think the safest approach is to set letter_title to the exhibition name, since it's prominently featured and the context of the letter.\\n\\nSo final answer:\\n\\n{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [\\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\"],\\n \\\"receiver_persons\\\": [\\\"Dr. W. Krasting\\\"],\\n \\\"send_date\\\": [\\\"1926-03-29\\\"],\\n \\\"sender_persons\\\": null\\n }\\n}\\n\\nWait, but the letter_title is in German. The example uses English, but the problem doesn't specify language. The instructions say \\\"extract the values\\\", so if the letter has German text, the title should be in German.\\n\\nThe schema doesn't specify language, so it's acceptable to have the title in German.\\n\\nYes, the user's example had an English title, but the actual letter's title is in German.\\n\\nTherefore, the letter_title should be [\\\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\\\"].\\n\\nThus, the JSON should include that.\\n\"}]},\"native_finish_reason\":\"stop\"}],\"created\":1769464990,\"model\":\"qwen/qwen3-vl-8b-thinking\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":8580,\"prompt_tokens\":1847,\"total_tokens\":10427,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":8514,\"rejected_prediction_tokens\":null,\"image_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0,\"video_tokens\":0},\"cost\":0.01835046,\"is_byok\":false,\"cost_details\":{\"upstream_inference_cost\":null,\"upstream_inference_prompt_cost\":0.00033246,\"upstream_inference_completions_cost\":0.018018}},\"provider\":\"Alibaba\"}"}, "scoring": null, "normalized_score": null}, {"_id": {"$oid": "69d4eb12b877594bc5718c0b"}, "test_id": "T0111", "benchmark": "business_letters", "date": "2026-01-26", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-04-02\"],\"letter_title\":[\"Betrifft Schifffahrt Basel-Rheinfelden\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Kur- und Verkehrsverein, Rheinfelden\",\"Basler Personenschiffahrtsgesellschaft, Basel\"]}}", "model": "gpt-5-mini-2025-08-07", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 7560, "output_tokens": 790, "total_tokens": 8350, "input_cost_usd": 0.00189, "output_cost_usd": 0.00158, "estimated_cost_usd": 0.00347}, "duration": 18.336063146591187, "timestamp": "2026-01-26T23:35:56.745366", "parsed": {"metadata": {"send_date": ["1928-04-02"], "letter_title": ["Betrifft Schifffahrt Basel-Rheinfelden"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Kur- und Verkehrsverein, Rheinfelden", "Basler Personenschiffahrtsgesellschaft, Basel"], "document_number": "letter22"}}, "conversation_id": "8598f3fb-3d5b-49f5-a473-0f5c396a4502", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 2, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D2PTKlt4W7g7GQZBJFZC95jYqIc1z\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1928-04-02\\\"],\\\"letter_title\\\":[\\\"Betrifft Schifffahrt Basel-Rheinfelden\\\"],\\\"sender_persons\\\":[\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"],\\\"receiver_persons\\\":[\\\"Kur- und Verkehrsverein, Rheinfelden\\\",\\\"Basler Personenschiffahrtsgesellschaft, Basel\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-04-02\"],\"letter_title\":[\"Betrifft Schifffahrt Basel-Rheinfelden\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Kur- und Verkehrsverein, Rheinfelden\",\"Basler Personenschiffahrtsgesellschaft, Basel\"]}}}}],\"created\":1769466942,\"model\":\"gpt-5-mini-2025-08-07\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":790,\"prompt_tokens\":7560,\"total_tokens\":8350,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":704,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.5, "f1_micro": 0.51, "cost_summary": {"total_input_tokens": 201080, "total_output_tokens": 56561, "total_tokens": 257641, "input_cost_usd": 0.050270000000000016, "output_cost_usd": 0.11312200000000003, "total_cost_usd": 0.16339200000000004}}, "normalized_score": 50.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c1a"}, "test_id": "T0115", "benchmark": "business_letters", "date": "2026-01-26", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5-nano", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-04-04\"],\"letter_title\":[\"EINSCHREIBEN\"],\"sender_persons\":[\"Basler Personenschiffahrtgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"]}}", "model": "gpt-5-nano-2025-08-07", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 4906, "output_tokens": 2633, "total_tokens": 7539, "input_cost_usd": 0.0002453, "output_cost_usd": 0.0010532, "estimated_cost_usd": 0.0012985}, "duration": 29.589850902557373, "timestamp": "2026-01-26T23:04:52.591438", "parsed": {"metadata": {"send_date": ["1928-04-04"], "letter_title": ["EINSCHREIBEN"], "sender_persons": ["Basler Personenschiffahrtgesellschaft"], "receiver_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "document_number": "letter24"}}, "conversation_id": "a8aee16b-b93f-4998-a8f3-beab9afb5f15", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D2Oz4sf8yS2l3Wy5bC3Pd4HiMUt7q\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\": {\\\"send_date\\\": [\\\"1928-04-04\\\"], \\\"letter_title\\\": [\\\"EINSCHREIBEN\\\"], \\\"sender_persons\\\": [\\\"Basler Personenschiffahrtgesellschaft\\\"], \\\"receiver_persons\\\": [\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-04-04\"],\"letter_title\":[\"EINSCHREIBEN\"],\"sender_persons\":[\"Basler Personenschiffahrtgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"]}}}}],\"created\":1769465066,\"model\":\"gpt-5-nano-2025-08-07\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":2633,\"prompt_tokens\":4906,\"total_tokens\":7539,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":2560,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.55, "f1_micro": 0.64, "cost_summary": {"total_input_tokens": 89515, "total_output_tokens": 65516, "total_tokens": 155031, "input_cost_usd": 0.00447575, "output_cost_usd": 0.0262064, "total_cost_usd": 0.030682150000000002}}, "normalized_score": 55.00000000000001}, {"_id": {"$oid": "69d4eb12b877594bc5718c08"}, "test_id": "T0245", "benchmark": "business_letters", "date": "2026-01-26", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "qwen/qwen3-vl-8b-thinking", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-02-16\"],\"letter_title\":[\"Proposal for Cooperation Regarding the 'Vogel - Gryff' Boat\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\",\"Gundolf\",\"Dr. Ryniker\"],\"receiver_persons\":[\"Herrn Christ\",\"Paravicini, Christ & Co.\"]}}", "model": "qwen/qwen3-vl-8b-thinking", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 4742, "output_tokens": 664, "total_tokens": 5406}, "duration": 15.186940670013428, "timestamp": "2026-01-26T23:05:18.005671", "parsed": {"metadata": {"send_date": ["1926-02-16"], "letter_title": ["Proposal for Cooperation Regarding the 'Vogel - Gryff' Boat"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft", "Gundolf", "Dr. Ryniker"], "receiver_persons": ["Herrn Christ", "Paravicini, Christ & Co."], "document_number": "letter01"}}, "conversation_id": "1e4493f7-eeec-4778-a793-07b21caad078", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 3, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"gen-1769465103-NzAFKDIH80C5dWt4Yf0d\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [\\\"Proposal for Cooperation Regarding the 'Vogel - Gryff' Boat\\\"],\\n \\\"receiver_persons\\\": [\\\"Herrn Christ\\\", \\\"Paravicini, Christ & Co.\\\"],\\n \\\"send_date\\\": [\\\"1926-02-16\\\"],\\n \\\"sender_persons\\\": [\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\", \\\"Gundolf\\\", \\\"Dr. Ryniker\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1926-02-16\"],\"letter_title\":[\"Proposal for Cooperation Regarding the 'Vogel - Gryff' Boat\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\",\"Gundolf\",\"Dr. Ryniker\"],\"receiver_persons\":[\"Herrn Christ\",\"Paravicini, Christ & Co.\"]}},\"reasoning\":\"I need to analyze this historical letter to extract the required metadata: letter_title, sender_persons, send_date, and receiver_persons.\\n\\nLet's analyze the document:\\n\\nFirst, I'll identify the sender. At the top of the first page, I can see the company name:\\n\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\" \\nThis is the sending organization.\\n\\nLooking at the date: The first page shows \\\"Basel, den 16. Februar 1926.\\\" which is February 16, 1926.\\n\\nFor the receiver, I see the address \\\"Herrn Christ, i/Fs. Paravicini, Christ & Co., Basel. Kauhausgasse 7.\\\"\\n\\nThe letter is signed by \\\"Gesamtleitung Basler Rheinschiffahrt-Aktiengesellschaft\\\" with signatures from \\\"Gundolf\\\" and \\\"Dr. Ryniker\\\" on page 3.\\n\\nThe letter appears to be a business letter about a boat (\\\"Vogel - Gryff\\\") that the company is building and discussing cooperation with Paravicini, Christ & Co.\\n\\nLet's break it down:\\n\\n- letter_title: This is a business letter discussing boat cooperation between Basler Rheinschiffahrt-Aktiengesellschaft and Paravicini, Christ & Co. The title could be \\\"Proposal for Cooperation Regarding the 'Vogel-Gryff' Boat\\\".\\n\\n- sender_persons: The sending organization is \\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\" (Basel Rhine Shipping Company). It's signed by Gundolf and Dr. Ryniker.\\n\\n- send_date: The date is clearly \\\"16. Februar 1926\\\" which in ISO format is \\\"1926-02-16\\\".\\n\\n- receiver_persons: The receiver is \\\"Herrn Christ, i/Fs. Paravicini, Christ & Co.\\\"\\n\\nLet me double-check:\\n- letter_title: Based on the content, it's about a proposal for cooperation regarding a boat\\n- sender_persons: \\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\" (with signatures from Gundolf and Dr. Ryniker)\\n- send_date: 1926-02-16\\n- receiver_persons: \\\"Herrn Christ, i/Fs. Paravicini, Christ & Co.\\\"\\n\\nThis seems to match the requirements.\\n\\nI'll format this according to the specified schema:\\n\\n{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [\\\"Proposal for Cooperation Regarding the 'Vogel-Gryff' Boat\\\"],\\n \\\"sender_persons\\\": [\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\", \\\"Gundolf\\\", \\\"Dr. Ryniker\\\"],\\n \\\"send_date\\\": [\\\"1926-02-16\\\"],\\n \\\"receiver_persons\\\": [\\\"Herrn Christ\\\", \\\"Paravicini, Christ & Co.\\\"]\\n }\\n}\\n\",\"reasoning_details\":[{\"format\":\"unknown\",\"index\":0,\"type\":\"reasoning.text\",\"text\":\"I need to analyze this historical letter to extract the required metadata: letter_title, sender_persons, send_date, and receiver_persons.\\n\\nLet's analyze the document:\\n\\nFirst, I'll identify the sender. At the top of the first page, I can see the company name:\\n\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\" \\nThis is the sending organization.\\n\\nLooking at the date: The first page shows \\\"Basel, den 16. Februar 1926.\\\" which is February 16, 1926.\\n\\nFor the receiver, I see the address \\\"Herrn Christ, i/Fs. Paravicini, Christ & Co., Basel. Kauhausgasse 7.\\\"\\n\\nThe letter is signed by \\\"Gesamtleitung Basler Rheinschiffahrt-Aktiengesellschaft\\\" with signatures from \\\"Gundolf\\\" and \\\"Dr. Ryniker\\\" on page 3.\\n\\nThe letter appears to be a business letter about a boat (\\\"Vogel - Gryff\\\") that the company is building and discussing cooperation with Paravicini, Christ & Co.\\n\\nLet's break it down:\\n\\n- letter_title: This is a business letter discussing boat cooperation between Basler Rheinschiffahrt-Aktiengesellschaft and Paravicini, Christ & Co. The title could be \\\"Proposal for Cooperation Regarding the 'Vogel-Gryff' Boat\\\".\\n\\n- sender_persons: The sending organization is \\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\" (Basel Rhine Shipping Company). It's signed by Gundolf and Dr. Ryniker.\\n\\n- send_date: The date is clearly \\\"16. Februar 1926\\\" which in ISO format is \\\"1926-02-16\\\".\\n\\n- receiver_persons: The receiver is \\\"Herrn Christ, i/Fs. Paravicini, Christ & Co.\\\"\\n\\nLet me double-check:\\n- letter_title: Based on the content, it's about a proposal for cooperation regarding a boat\\n- sender_persons: \\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\" (with signatures from Gundolf and Dr. Ryniker)\\n- send_date: 1926-02-16\\n- receiver_persons: \\\"Herrn Christ, i/Fs. Paravicini, Christ & Co.\\\"\\n\\nThis seems to match the requirements.\\n\\nI'll format this according to the specified schema:\\n\\n{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [\\\"Proposal for Cooperation Regarding the 'Vogel-Gryff' Boat\\\"],\\n \\\"sender_persons\\\": [\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\", \\\"Gundolf\\\", \\\"Dr. Ryniker\\\"],\\n \\\"send_date\\\": [\\\"1926-02-16\\\"],\\n \\\"receiver_persons\\\": [\\\"Herrn Christ\\\", \\\"Paravicini, Christ & Co.\\\"]\\n }\\n}\\n\"}]},\"native_finish_reason\":\"stop\"}],\"created\":1769465103,\"model\":\"qwen/qwen3-vl-8b-thinking\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":664,\"prompt_tokens\":4742,\"total_tokens\":5406,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":577,\"rejected_prediction_tokens\":null,\"image_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0,\"video_tokens\":0},\"cost\":0.00224796,\"is_byok\":false,\"cost_details\":{\"upstream_inference_cost\":null,\"upstream_inference_prompt_cost\":0.00085356,\"upstream_inference_completions_cost\":0.0013944}},\"provider\":\"Alibaba\"}"}, "scoring": null, "normalized_score": null}, {"_id": {"$oid": "69d4eb12b877594bc5718c18"}, "test_id": "T0489", "benchmark": "business_letters", "date": "2026-01-26", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5.2-2025-12-11", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-02-23\"],\"letter_title\":[\"\"],\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft (Der Pr\u00e4sident)\"],\"receiver_persons\":[\"\"]}}", "model": "gpt-5.2-2025-12-11", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 2256, "output_tokens": 50, "total_tokens": 2306, "input_cost_usd": 0.003948, "output_cost_usd": 0.0007, "estimated_cost_usd": 0.004648}, "duration": 4.548861503601074, "timestamp": "2026-01-26T02:04:28.515821", "parsed": {"metadata": {"send_date": ["1928-02-23"], "letter_title": [""], "sender_persons": ["Basler Personenschiffahrtsgesellschaft (Der Pr\u00e4sident)"], "receiver_persons": [""], "document_number": "letter15"}}, "conversation_id": "46f6d95f-a3f1-4231-a4f3-b95866e99b7b", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D25JhCXkK5YAB5JrSz89ujx8JUTuL\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1928-02-23\\\"],\\\"letter_title\\\":[\\\"\\\"],\\\"sender_persons\\\":[\\\"Basler Personenschiffahrtsgesellschaft (Der Pr\u00e4sident)\\\"],\\\"receiver_persons\\\":[\\\"\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-02-23\"],\"letter_title\":[\"\"],\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft (Der Pr\u00e4sident)\"],\"receiver_persons\":[\"\"]}}}}],\"created\":1769389465,\"model\":\"gpt-5.2-2025-12-11\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":50,\"prompt_tokens\":2256,\"total_tokens\":2306,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.56, "f1_micro": 0.57, "cost_summary": {"total_input_tokens": 201080, "total_output_tokens": 3276, "total_tokens": 204356, "input_cost_usd": 0.35189000000000004, "output_cost_usd": 0.04586400000000001, "total_cost_usd": 0.3977540000000001}}, "normalized_score": 56.00000000000001}, {"_id": {"$oid": "69d4eb12b877594bc5718c10"}, "test_id": "T0490", "benchmark": "business_letters", "date": "2026-01-26", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5.2-2025-12-11", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-09-25\"],\"letter_title\":[\"> Darlehen von Fr. 33'000.\u2013 (Personenschiffahrtsbetrieb)\"],\"sender_persons\":[\"> Der Unterzeichnete (Name nicht ersichtlich)\"],\"receiver_persons\":[\"> Basler Rheinschiffahrt Aktiengesellschaft, Direktion\"]}}", "model": "gpt-5.2-2025-12-11", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 2256, "output_tokens": 81, "total_tokens": 2337, "cached_tokens": 1536, "input_cost_usd": 0.003948, "output_cost_usd": 0.001134, "estimated_cost_usd": 0.005082}, "duration": 4.914438724517822, "timestamp": "2026-01-26T02:09:29.019837", "parsed": {"metadata": {"send_date": ["1932-09-25"], "letter_title": ["> Darlehen von Fr. 33'000.\u2013 (Personenschiffahrtsbetrieb)"], "sender_persons": ["> Der Unterzeichnete (Name nicht ersichtlich)"], "receiver_persons": ["> Basler Rheinschiffahrt Aktiengesellschaft, Direktion"], "document_number": "letter51"}}, "conversation_id": "31fa959d-19a5-4def-8c68-80783a74c9b1", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D25OX15HHQPTpejaEuPvjdXzsNx5I\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1932-09-25\\\"],\\\"letter_title\\\":[\\\"> Darlehen von Fr. 33'000.\u2013 (Personenschiffahrtsbetrieb)\\\"],\\\"sender_persons\\\":[\\\"> Der Unterzeichnete (Name nicht ersichtlich)\\\"],\\\"receiver_persons\\\":[\\\"> Basler Rheinschiffahrt Aktiengesellschaft, Direktion\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1932-09-25\"],\"letter_title\":[\"> Darlehen von Fr. 33'000.\u2013 (Personenschiffahrtsbetrieb)\"],\"sender_persons\":[\"> Der Unterzeichnete (Name nicht ersichtlich)\"],\"receiver_persons\":[\"> Basler Rheinschiffahrt Aktiengesellschaft, Direktion\"]}}}}],\"created\":1769389765,\"model\":\"gpt-5.2-2025-12-11\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":81,\"prompt_tokens\":2256,\"total_tokens\":2337,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":1536}}}"}, "scoring": {"f1_macro": 0.49, "f1_micro": 0.58, "cost_summary": {"total_input_tokens": 74080, "total_output_tokens": 1483, "total_tokens": 75563, "input_cost_usd": 0.12964000000000006, "output_cost_usd": 0.020761999999999996, "total_cost_usd": 0.150402}}, "normalized_score": 49.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c22"}, "test_id": "T0108", "benchmark": "business_letters", "date": "2026-01-26", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-05-03\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":[\"Dr. Max Vischer\"]}}", "model": "gpt-5-2025-08-07", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 1398, "output_tokens": 2032, "total_tokens": 3430, "cached_tokens": 1280, "input_cost_usd": 0.0017475, "output_cost_usd": 0.020319999999999998, "estimated_cost_usd": 0.022067499999999997}, "duration": 44.25947403907776, "timestamp": "2026-01-26T23:21:03.829525", "parsed": {"metadata": {"send_date": ["1928-05-03"], "letter_title": null, "sender_persons": null, "receiver_persons": ["Dr. Max Vischer"], "document_number": "letter31"}}, "conversation_id": "92213dbb-b641-499b-a6f8-0ea3b101e349", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D2PEUETJ6lNe5q5MoCIq7jHjJEhR4\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1928-05-03\\\"],\\\"letter_title\\\":null,\\\"sender_persons\\\":null,\\\"receiver_persons\\\":[\\\"Dr. Max Vischer\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-05-03\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":[\"Dr. Max Vischer\"]}}}}],\"created\":1769466022,\"model\":\"gpt-5-2025-08-07\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":2032,\"prompt_tokens\":1398,\"total_tokens\":3430,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":1984,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":1280}}}"}, "scoring": {"f1_macro": 0.63, "f1_micro": 0.69, "cost_summary": {"total_input_tokens": 116996, "total_output_tokens": 97704, "total_tokens": 214700, "input_cost_usd": 0.14624500000000007, "output_cost_usd": 0.97704, "total_cost_usd": 1.1232849999999996}}, "normalized_score": 63.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c2e"}, "test_id": "T0136", "benchmark": "business_letters", "date": "2026-01-26", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "o3", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-03-01\"],\"letter_title\":[\"Betrifft Ihr Schreiben vom 27. Februar\"],\"sender_persons\":null,\"receiver_persons\":null}}", "model": "o3-2025-04-16", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 2438, "output_tokens": 254, "total_tokens": 2692, "cached_tokens": 1664, "input_cost_usd": 0.004876, "output_cost_usd": 0.002032, "estimated_cost_usd": 0.006908}, "duration": 8.612407684326172, "timestamp": "2026-01-26T23:49:32.329843", "parsed": {"metadata": {"send_date": ["1928-03-01"], "letter_title": ["Betrifft Ihr Schreiben vom 27. Februar"], "sender_persons": null, "receiver_persons": null, "document_number": "letter17"}}, "conversation_id": "80596a5e-b546-4192-a587-791c90221faa", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D2Pgck2aGGg8ozvIhfHqeXz0NarRQ\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1928-03-01\\\"],\\\"letter_title\\\":[\\\"Betrifft Ihr Schreiben vom 27. Februar\\\"],\\\"sender_persons\\\":null,\\\"receiver_persons\\\":null}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-03-01\"],\"letter_title\":[\"Betrifft Ihr Schreiben vom 27. Februar\"],\"sender_persons\":null,\"receiver_persons\":null}}}}],\"created\":1769467766,\"model\":\"o3-2025-04-16\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":254,\"prompt_tokens\":2438,\"total_tokens\":2692,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":192,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":1664}}}"}, "scoring": {"f1_macro": 0.66, "f1_micro": 0.62, "cost_summary": {"total_input_tokens": 77041, "total_output_tokens": 19216, "total_tokens": 96257, "input_cost_usd": 0.15408200000000005, "output_cost_usd": 0.15372799999999998, "total_cost_usd": 0.30781000000000003}}, "normalized_score": 66.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c11"}, "test_id": "T0491", "benchmark": "business_letters", "date": "2026-01-26", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5.2-2025-12-11", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-10-10\"],\"letter_title\":[\": Verein f\u00fcr die Schiffahrt auf dem Oberrhein\"],\"sender_persons\":[\": Jean Frey\"],\"receiver_persons\":[\": Dr. Max Vischer\"]}}", "model": "gpt-5.2-2025-12-11", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 2256, "output_tokens": 57, "total_tokens": 2313, "cached_tokens": 1536, "input_cost_usd": 0.003948, "output_cost_usd": 0.0007980000000000001, "estimated_cost_usd": 0.004746}, "duration": 4.2370030879974365, "timestamp": "2026-01-26T02:12:24.579993", "parsed": {"metadata": {"send_date": ["1932-10-10"], "letter_title": [": Verein f\u00fcr die Schiffahrt auf dem Oberrhein"], "sender_persons": [": Jean Frey"], "receiver_persons": [": Dr. Max Vischer"], "document_number": "letter55"}}, "conversation_id": "675db36b-996a-4760-9619-8466bd4f2107", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"chatcmpl-D25RNrqGEPCAhYiSruirMannHxWDY\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1932-10-10\\\"],\\\"letter_title\\\":[\\\": Verein f\u00fcr die Schiffahrt auf dem Oberrhein\\\"],\\\"sender_persons\\\":[\\\": Jean Frey\\\"],\\\"receiver_persons\\\":[\\\": Dr. Max Vischer\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1932-10-10\"],\"letter_title\":[\": Verein f\u00fcr die Schiffahrt auf dem Oberrhein\"],\"sender_persons\":[\": Jean Frey\"],\"receiver_persons\":[\": Dr. Max Vischer\"]}}}}],\"created\":1769389941,\"model\":\"gpt-5.2-2025-12-11\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":57,\"prompt_tokens\":2256,\"total_tokens\":2313,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":1536}}}"}, "scoring": {"f1_macro": 0.58, "f1_micro": 0.54, "cost_summary": {"total_input_tokens": 127000, "total_output_tokens": 1848, "total_tokens": 128848, "input_cost_usd": 0.22225000000000006, "output_cost_usd": 0.025872, "total_cost_usd": 0.24812199999999995}}, "normalized_score": 57.99999999999999}, {"_id": {"$oid": "69d4eb12b877594bc5718c09"}, "test_id": "T0116", "benchmark": "business_letters", "date": "2026-01-26", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5-nano", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-03-22\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"Basler Personenschifffahrtsgesellschaft\"]}}", "model": "gpt-5-nano-2025-08-07", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 9324, "output_tokens": 1980, "total_tokens": 11304, "input_cost_usd": 0.00046620000000000006, "output_cost_usd": 0.0007920000000000001, "estimated_cost_usd": 0.0012582000000000001}, "duration": 25.2205171585083, "timestamp": "2026-01-26T23:15:23.331230", "parsed": {"metadata": {"send_date": ["1928-03-22"], "letter_title": ["null"], "sender_persons": ["null"], "receiver_persons": ["Basler Personenschifffahrtsgesellschaft"], "document_number": "letter19"}}, "conversation_id": "c3e9197c-574f-4018-86e3-e766111c4735", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D2P9LYMoHcUs3oznzDeIPiWPQRs9W\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\": {\\\"send_date\\\": [\\\"1928-03-22\\\"] , \\\"letter_title\\\": [\\\"null\\\"], \\\"sender_persons\\\": [\\\"null\\\"], \\\"receiver_persons\\\": [\\\"Basler Personenschifffahrtsgesellschaft\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-03-22\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"Basler Personenschifffahrtsgesellschaft\"]}}}}],\"created\":1769465703,\"model\":\"gpt-5-nano-2025-08-07\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":1980,\"prompt_tokens\":9324,\"total_tokens\":11304,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":1920,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.5, "f1_micro": 0.47, "cost_summary": {"total_input_tokens": 154783, "total_output_tokens": 72779, "total_tokens": 227562, "input_cost_usd": 0.007739149999999999, "output_cost_usd": 0.029111600000000005, "total_cost_usd": 0.03685075000000001}}, "normalized_score": 50.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c12"}, "test_id": "T0134", "benchmark": "business_letters", "date": "2026-01-26", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "o3", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-05-10\"],\"letter_title\":[\"Betr. Abrechnung\"],\"sender_persons\":null,\"receiver_persons\":null}}", "model": "o3-2025-04-16", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 1463, "output_tokens": 581, "total_tokens": 2044, "input_cost_usd": 0.002926, "output_cost_usd": 0.004648, "estimated_cost_usd": 0.007574000000000001}, "duration": 15.492307424545288, "timestamp": "2026-01-26T23:32:02.916556", "parsed": {"metadata": {"send_date": ["1928-05-10"], "letter_title": ["Betr. Abrechnung"], "sender_persons": null, "receiver_persons": null, "document_number": "letter34"}}, "conversation_id": "df6ba821-83fa-4329-985b-ffc8c03688ce", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D2PPYYURTkbOoBfwsZroSKJs3p1ly\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1928-05-10\\\"],\\\"letter_title\\\":[\\\"Betr. Abrechnung\\\"],\\\"sender_persons\\\":null,\\\"receiver_persons\\\":null}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-05-10\"],\"letter_title\":[\"Betr. Abrechnung\"],\"sender_persons\":null,\"receiver_persons\":null}}}}],\"created\":1769466708,\"model\":\"o3-2025-04-16\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":581,\"prompt_tokens\":1463,\"total_tokens\":2044,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":512,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.6, "f1_micro": 0.65, "cost_summary": {"total_input_tokens": 123366, "total_output_tokens": 35795, "total_tokens": 159161, "input_cost_usd": 0.2467320000000002, "output_cost_usd": 0.28636, "total_cost_usd": 0.5330920000000002}}, "normalized_score": 60.0}, {"_id": {"$oid": "69d4eb12b877594bc5718bd2"}, "test_id": "T0500", "benchmark": "business_letters", "date": "2026-01-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-3-flash-preview", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-03-24\"],\"letter_title\":null,\"sender_persons\":[\"A. M\u00fcller\",\"W. ... \"],\"receiver_persons\":[\"P. Christ-Wackernagel\"]}}", "model": "gemini-3-flash-preview", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 1428, "output_tokens": 94, "total_tokens": 64432, "input_cost_usd": 0.000714, "output_cost_usd": 0.00028199999999999997, "estimated_cost_usd": 0.000996}, "duration": 346.6381645202637, "timestamp": "2026-01-25T00:49:27.291411", "parsed": {"metadata": {"send_date": ["1926-03-24"], "letter_title": null, "sender_persons": ["A. M\u00fcller", "W. ... "], "receiver_persons": ["P. Christ-Wackernagel"], "document_number": "letter03"}}, "conversation_id": "8ba7b725-fcc6-4a76-b47e-6126e932ece8", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 2, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Sat, 24 Jan 2026 23:49:27 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=346424\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"video_metadata\":null,\"thought\":null,\"inline_data\":null,\"file_data\":null,\"thought_signature\":\"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\\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1926-03-24\\\"\\n ],\\n \\\"letter_title\\\": null,\\n \\\"sender_persons\\\": [\\n \\\"A. M\u00fcller\\\",\\n \\\"W. ... \\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"P. Christ-Wackernagel\\\"\\n ]\\n }\\n}\"}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"url_context_metadata\":null,\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null}],\"create_time\":null,\"model_version\":\"gemini-3-flash-preview\",\"prompt_feedback\":null,\"response_id\":\"h1p1acT3CPODkdUP0ZrbmAw\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":94,\"candidates_tokens_details\":null,\"prompt_token_count\":1428,\"prompt_tokens_details\":[{\"modality\":\"IMAGE\",\"token_count\":1092},{\"modality\":\"TEXT\",\"token_count\":336}],\"thoughts_token_count\":62910,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":64432,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1926-03-24\"],\"letter_title\":null,\"sender_persons\":[\"A. M\u00fcller\",\"W. ... \"],\"receiver_persons\":[\"P. Christ-Wackernagel\"]}}}"}, "scoring": {"f1_macro": 0.64, "f1_micro": 0.66, "cost_summary": {"total_input_tokens": 126168, "total_output_tokens": 3017, "total_tokens": 129185, "input_cost_usd": 0.06308399999999996, "output_cost_usd": 0.009051000000000003, "total_cost_usd": 0.072135}}, "normalized_score": 64.0}, {"_id": {"$oid": "69d4eb12b877594bc5718bff"}, "test_id": "T0268", "benchmark": "business_letters", "date": "2026-01-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "x-ai/grok-4", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-05-24\"],\"letter_title\":null,\"sender_persons\":[\"Dr. Rud Spech\"],\"receiver_persons\":[\"Dr. Hans Fischer\"]}}", "model": "x-ai/grok-4", "provider": "openrouter", "finish_reason": "stop", "usage": {"input_tokens": 1715, "output_tokens": 6556, "total_tokens": 8271, "cached_tokens": 1198, "input_cost_usd": 0.005145, "output_cost_usd": 0.09834, "estimated_cost_usd": 0.103485}, "duration": 121.79090762138367, "timestamp": "2026-01-25T14:38:38.068519", "parsed": {"metadata": {"send_date": ["1932-05-24"], "letter_title": null, "sender_persons": ["Dr. Rud Spech"], "receiver_persons": ["Dr. Hans Fischer"], "document_number": "letter39"}}, "conversation_id": "789fcc32-f361-4719-9dda-274cb886bd4c", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"gen-1769348196-jYsYlCWORQZ1mOqdCE1L\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\" {\\\"metadata\\\":{\\\"send_date\\\":[\\\"1932-05-24\\\"],\\\"letter_title\\\":null,\\\"sender_persons\\\":[\\\"Dr. Rud Spech\\\"],\\\"receiver_persons\\\":[\\\"Dr. Hans Fischer\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1932-05-24\"],\"letter_title\":null,\"sender_persons\":[\"Dr. Rud Spech\"],\"receiver_persons\":[\"Dr. Hans Fischer\"]}},\"reasoning\":null,\"reasoning_details\":[{\"id\":\"rs_0ea392ab-dcf6-431a-2c39-17105f94e30b\",\"format\":\"xai-responses-v1\",\"index\":0,\"type\":\"reasoning.encrypted\",\"data\":\"OPL8yZvQbmsx3rZ9JgZvzEh24tJGs/sLjC5uGt19n8r8BTOb1Y2zbJQ//7CzMnSRiYOlf1SERYkAbHJg/bV09QnJ/waSFcqPsulNaRG0NhZaQWUyKOncsdlT7a3OzRpe03JMl0iy1fFVOi1uiaEdc44J1XeGkcPzpnz4G++c1FzUCTuj8bIIfQM+05K7Jjy1Ylzaoqgau9pTYL6kKdP9Hf0Z6gAcRN0zHhP5fR1WIaT0izajLemRQGqunVCjyi9uLA9VZ/jhPTJWsUNlrqrpKSm+m5MJZ4e8ZkH6eaTgSf3R1Vx2N8MZ7DxvmAYdz2ls9mUDlxEagz0iq+HUEs1DbLXS+MZ+xxNr5oj7peqzUxz6iMkCVv7bI7EScpNefCjKtGH+tOYKByk85t2bYKI7N3ZWEqpD/DVFN+KgWUvhG5Nt48gkNDBMqcuGdnJhT8Ftv9EwNOKzM/11SBCxXRzuMgwhTlQQUwXU+7azbhAQrse8J2/No6zc5GdfVZuJY8LtTsVp2L+AV3wtk0qHGmx6Nj3dykDD+Q7vyI/TOVVvWVvBfXJovgdUdaMg1BFu+IrZO6oaFvrFwLDJa/+03vW1bMONjEac1k6hPQm+Jr01ywpWeN0P2APpeyCTX3XKHYOLPrtzCpXUeVzWeke9d74EoAGIqqkydI/4RaqYSGFMipeamY6lG8aS3aG+DYvrByCsqm5QFXgIjZfqpzak/2eNgUMniNdAU1Mhl6Avoy7u6NlUGADdH/xX/cep1jK7YcS/fZSLEBU25RghoMFaNtBzHnsIcov18YVlSnEmI3gYN63a7lQyhNgU5hEaJp2PPdxnAy9WWHsBrL59K7SJ6n/orKPZFHh+nij5SqXwLyBFkb3XdCmAje2Lv4qVm6xNx8X/jjELNX5yPj8oDMO/2lo5u5L2n7hGQ7vw9oDLWtAItN+BWK9KkUZEROBFcfX5ArWh2UWnoUVgMDUyV14wnU/q8OBDs4J+viDTyxFx0Bz4rCgjbRUTvvmx0D4p7GbKQXaiK2PgYbU1UR9w1bTe+IA62bgvez0MW7RP41UcpdVuR0B4JTyjzoKB8D42VnNWiEXZBqkj4OWGRfoZ9R7Jg29hQpTRyMCui+e5VHz8cIb16jvtCVWc4u3c7K1kyTsGaUpmqxkNSsRMhFEcVs+FnUbqXvrJz2bkKU3woMxh6WQdU+YGGd6UHPmo9N98ugfc+XU4hI+qbB7xFje75oqNX0FZAdv69V5Opoq8cPsvjo35wtrBK29vOzdtBMZxJOzpraySaRNAPee/Io5J4lUZiy97S/+KASNu9WNOvCL5D0pdwbmiiLp5eyMDy3jIm12upTOmgHH4/QgD6aspSEXbX+SphMyasGJA+p6Li8xxDmagf/TfaKNT1c7bcXsm4Fcn0v1FO9IOIvLdH8/71Tq6+VqjcW/jrlCBtLJJJQ5i52oXoUESRLKKji7mAVFNuw+rdBuJj4LVMyBnOvTY0/zpEuJ6ONlpBgFoifRKivy8PLC9dY7OvdvIFOcIQkbCq7rr/lyPnzqK4Z9cO6KKRHhX2ZkIuCrk79uvYQeI6jpAWBnM4A7r7GRUnQL/rAOEW1ZRJAyt85aEaJodxGuJ0gytMELACYo6RJMbHSlZtXVmQCq0OQEoba4In7wuwFeM5pd79RcoVnUkvV8mkdR1qP3s42Ok7Nkqc5EQ7P6ukN22hfOP33/Mkk87Uy3763/4Y9bMcjrmbOfPYkOvvysIbZM6rXnZF6/ke4nvuM6CvUxiygTdL39iAqOWovSJdTNYcVmelvpOMUzbkpUv8lZgUp6mjxDe7Fpm1WAMwYvCXCEA2mJNWwdYi8tCRd67mY0JMTKLGZXF3jrzattt7Dq7BQAjHhdAgidmzoDibbI2N5gpdnHGDupIX3ZUvI5cWOWE/e9/f+D4DOka8swXFSBhx1/0KV9POdpKC5A2UVjnBCGkoasvm4jKETCVhN0KYUgSDf8ipPC8vSLVA7a3Jmh1lzxuZ66X2DTeqTTexqPg5ywyvyhhPmRDAyrg+INs4TVHj/wnp+dE/GCNc9MAT6hluS9FkCtKkK24tEZNc6NPfjxHyYw9pwV/ZwNfoj853hjjqGYc4u5lyCbxVDwKvdrqdxOeOz00ShW3KX0EL+Zp9e28h4YM5ySccN+AJ4Fufp4cqhIVLYeVKoSIgSG5Xa5e276K+ysQc24UiBgTQJJ7A7iaHT9pJjJCFli79d0QIlVwJ3LYWXthC2yimJwnC8HVChF1RlJjN5orzV0Kh9z40SgD1sRFnAvpIgobXa8rgyzWpT/EgEL92+/MhdyePp+NFYIiCi3s0m2sb1EavnC1wFj1oVswgxyQnVJbLgF7N+nKhZrMyzaXNfWnK6ix1IIdaq4anAKjnS0nXQrKa5YnhRf7LzkgHHkgK3OJiaoVSTbxoQHV+dQmHLs0JOvpCr4AwqLF+NvSfgkk513ArE4bOES84gvcOelOCnPSCN4fVfWPHho4isy+VDsrghTJH/WAi265HUbg6QN+evssIGSdbpjABZFrsZChnqwtzJZoiYAB8duwEUJhlNUBjrMIDiXMKVJ2YNEg4Ok6y+xS5GcZljufsrY4jQdDDkKUY1fhSiu/748sQIZnH71E95S0P/jrqQOrqBrTJ+vuwhdanG8aIwtmZC7qGjs6OOEkAG87tHh8aB7h9rRlvIUeC1tHmBdf09KUJvqS3M/IhiaxuVwfBMNKpAWWeW9OJUuwk/zDrFf/GVC03Gu1cyFfM0RnvL3A4wJijpe6DGLaP/tfq99hNtt/PElsR6kxBv/znTKil/F6FN6Md3jiqJbdwf39PPg/GS2Qy2BswCWgAwSdWkv3lzKwVhpMgu+19S4HvbCAaUG6Vk5nDYfKNxH9bJPct0gSR5ybiXTQKDhbzapS1WSuP5wA/j9fZOejo1G6qEmTmtrQfVUemD1cjiCIdjjAj4uBRbFhh1ef3CckkBsDeP6dJxGCt8JdMqBM0YptO4kzeRBZY/0BNHrtCQiUGTlib1ECoykR8eC8TNnB8A93GwVFf9Bi2M7MpGwf+brVHOgyw5P9lUJ7ZIyFXd0D0UkgMLW+lYgObddiYxX8KFVw7PuvSRZJJ/vWcbMJxD0Q7q4qycirXyt+yrPjn38VHlIjVRAtJ5zn8Ud/hYd0oAP5CUZffCqmaaCJNXNQQ6MS6WiYxywKEVNQ6p89m1dsMcaW1emnTbU0LWufpR0bSzOCNt+j06IohY0hMmrvgXAsccndBIqHP1e5ZE+zEy6z05cJCzh2YMqhsku3T+3c5+Yo/80pASPPO2a1yWHE/h9kWXID2HnaUPVAkU+4AfhbSe98pXrjangsLuUVmsX40/lkpCS7ge68VvUmUTrXif8lzM7zp3kAn8MCht4RJiCeoaBfriOthfVXTsvVf27+UOH7vLWA7fHNmT1ApWS86O7xzYg4z66B1Y2969CLmv0Vqgt0crTnEVtYWwYd67yOdRmdhIjaV1Qoa9M9YzRDf0RwEkBzcTgGxbQKDqDh1I7py16BMxS3X8CQ8e+5jACFYqwAEiMZAWgvDgM2zvOHf5VqxN+GQgp+p1HHielc3+nvPy/Q+IPq67S1ybQRSlbJGzEJdISc82p9F3ZJ7ahl9DB+AWxEgnqUVjDtlf+h9v5Eha415aUb50mEj/Tt/z+w/q9D3TArO61d+JT1jpCI5vPVrmlfPun/wJIfxe/VnmUpPzdHmBVS0aCD0B7ubpsZpXJR412RJhsccqxQtVq8N+JaFL8Gha0oXB9fZ0zaS7562NI8H+bMR/x4r6FgRdG+2I9Al1I820ubFRYlwAwoFacmAegtdWIHqVad0NdVsQDaZDKuGa8Y9hwVQw3qUsN2K2pi2AA1kjipZK4TZhhhtNli/Bt9K9gvJUIm45KXQ1rCAoDA5Yo08v+3eUglzwu1IhzzjQ5NAcqFYb6aomy7zyFV4BSskNxiqzNyvvTsVkMPH1XSZpheCyseZh420p9Luj+VoT2RcGxCjc6ED+SPLLx8GUwIsWfxERliHx+qJXDpzL8zL7oI75oN2y3KzRBm7C/Mj6cb0RB2+v1HM7p4vsHN3BZ9GkAfbVkj0cBHLfjJLlPy7m4qzldQBSK1JNYAWGif3CT2GwD+Wpqyv1TlsLqtPjltGZ9S2LiXJj3suVq+0oE+HEUESP1bBJTRxBSvvTH4PHRIOxBpFf1tVFK7puohQOIBoj7hq4eddh7eyavYNPxPTttC1ooOYLRlicbH5tJPk887fno5FJo2Sh3DeYM7cne8edfdcAzWUA/LFDcw2itPDzxvdoHEzh0Z0JyBnZwRbRneDCi2VA7TcJoDwyOrnLhY7ME4yLJLWy7MZCTYOlovKfgXJp1LVonyfi5oufN8k89La5B3876tpaLJXHJEDnbX3+ATp/cBpaegnO2+kIE+/gPi02GYH6N2XsglwREdVmwNB3AT7WURF8xEto2sV9MfsUbydFKmkeltmsyY8G60DrDUHxxaJV153yt9jL98QGz8gs3ttyxQr5iIXZP4274tFX0JJmHrqsP0b8artE3MwJ9Le/B/vunZrl7SmxTjOZu34jyBAEb8t0JEfwfGa2+zLDv+Mv0+1CqFShRgavbKHxMPIoZSSLLAX9h2iTUWEgUJJbnR3tV85t2Q3wSabUDfITHOqEnKnFUi+aZyja3pFwPYK032BLIZZIbwlQ3mxs8YGEclh8zn+hWBELSOfBy8pJPvDL3l/DvbEz97PSR0LJezHhhrxzmDjDi/M9DFoXsAiDrtanATeawVCV413YF9BarPkw+EnVqGzs3YwlHU5h3ouSXyDT663Eq3afoCXGqKB69g7c5U7x8kvbqNMRXMmEIY1NmOd/zPE+23u+tBP496wKQKXyII+xtHJMVhp9UWfld3GIHKTwT7f/7eFT7vcvUCI1oaaXK3g5BJtmdQNaZrH0RchzTkcKBOC/MVw9lRN4nAEeHu4n6HK1x8dN5zZH0zURy+CHTxZ48ylEH40SA/GgAT1g9yTF25AXNmmpeC7sxbWg3KG56/AR/8vnKsUMDr9YeQD0VmkaDLqNM1FGs0Hw/+rhQrdWAqgKqlFcocQF/BP28UPPb8TIFB534BvhpvE0Slwel1bs0+U9UrHz2GbjvugwqaXDyXF1X71v7CrRIyja3mognN3X/krcaLkrADRBidsjtT8ldy2xpNbC4Yf7tC0HQrD+kQwFmf99rEs/DQDV+zSzns5sy9T8re0aVwGc+q2r1KY7a4pQ3eVDbXBwiGCdJDA3kv/pgjAC/ne4Dcf/Hes44bFhKjO2sHu2QfasJRKefX+x/Kgq+7yY2RTT6RFm1dNaPaBKpukNjX+GZ+VPnb5/lUzUwJlY8Ole6OCgjVpqbpNVzye9f5oQlUWaJMd805xYLTBLZPS9pfERG7q5KwzTWc+y33+AEbm977EjN0bXjAsKqSpuCW5GvPOzJyvSYMJS2IFBDlxCcz7F7qe8JPUGhKpDih2Mz/Lob/WfkdIrqnELPSrH8YKAn00/Jrfm6razsOcr72cNVJBDCt6/HStgrV3FGM55x1PSo+xf8phcyhRjjRm7oosyWACWJba545PI+iP9Nl//ZczSxlrzDc74+3uQ0tr9dQAzAgOfr82yqMdN7xdk8a11haVpTwrmXH6QqFGfMZDmc5kqmWwkc7FYXk5jdE11BwQVhzm6c5cOSbBlbXzFxikRcjYEearkbUaeCzv61e/QcQ5lshSXZSC9ESPsqaCp14ChoZDDiv6vqmMKYZDV4egcOvxgSmFCRgZ/O2mENi6BFLHjkUNnT6SYqfYl7aZNNs3JcOWrMGzmfqt9DmwSgAGUsT8PXJgYG1TihVKRoKnlMDlGb/4GnAUcyEGo2BlayBUBpItyO0AeTeBm5Px8IyNtSaLZCkSCOOd4x60WxBbONlRBhhI6g8Fllkjfo5dKSZ97fHdPhSYG1MDnO0CVzd1+Sre7kmndR08cFTI8IKFvmTYGqjnBZ3Ghp45g2b/f2QSnnosbufViGprLhOY0U1M41e8kqA6IJx8w+oUnixeCKZVwy8DjNTpScQCx74QjmmXZTnyDKMwO2FTcThTrEJjhnqxxn1Zc+4FSi7cERABVdBYh3D3sYX3Zq/v9lAMrTk+n43Y2aB1667CaoUMDJE3hC5hgmFYfvX3sENyHfIYRwUx2iEZPTuY5hCtUxMnMGutalXiA0NpEjqj8+VrDJ5m3Xh++t95wfGi3S8YHuUT9cZG+Fhosp5bc4REgQ7Uew8q9tZVfHG8jFMVmZueKYo2yft/cbeQTPeiAm1Lkf7MMei0qrkQTfBT0AQsEmyBcstgLmNrDokuAw7ACGc2V+A8o8lZnPGgKfXCCDuB4wG/Rhx3q4RYuqEk3aBA7war0ntl1I0SuXvu7W/Dnc6AELeQ7Hbm3ULtJ4rK5rGo51LTIaiYkn/XAWNOYrHRQ6NddrnLNRkr3DCtTWT4QEPhwtxRZL72fnofpTuli7QkVq2/fjREuj/9VWuEp9F+k0dNb21kZ796DMrBlkVF2XEXtIFFOLjLFr0sACCmRTVrUAojOlNi2YkbvxAP4+C3gviDZRcIKk7dC5bhxU/PIrplvw7Kcfo5Ht7PJJxVWlk0iJqXuSZPosXP8gc+f+hRRA+aGryfkrhwQxlK02kLrWr6SoWoeOJ1bumnvuyECNNVoqjNbeT/bNTL2/sW9gSNO1HiZndk0Z+T/6vQvn0T0mG96kY340idNVlfVD1QhjU6g+h5D6je8O6lNufgXaYSfpVfPMWxupFCWY1SE8B7tlVLbug+cDPGUAe6HC8N4R7WtUWU53/w3JQTVsFxUqtKAPaHzeVFz3N3dBBUoUUM+oLRLKf+ii10/nTWQC2xCoCRox91GRXthoQ/vYSf+ImzEk6YHyD0ZAIMsgpxuxh8j9IfS8Lzd/HzFauX3eQNk+M7HxV6/dlu3xCG6FPbughZh4hzArzZcNMF20tHNiQ41Wrprjde5r28CEYAzGq0NHhjDu6jg1cO1JiEgyiIwA+pWuYVoW4QiBLGzcFWJbYRK92OnqM/c4r7lwQ3Us7KbDK9NgO767sAWehQ91jeCBhoWJnyxj6LCD4Lp1aucwKOu5C89+YzTNs5Niva1nM0Ukd4NHsmP9rngpbbZdiJKEW4cFwFqGba74ytZRWquSH4ARgw7T7egEI14F2/kzlwJZyNxik7EWB2YenVfA2WtEpsETinpYUkR53FOaFHjdfj71rH9fMeWOgFGJ4Ia23Jf2coyjjBSQMokwxscem9gPyiXGRXS7MmJzKROYSFyHLmTf7CGR9qoeLob3k4u8ocx5Y0zcc/OelbXIYupExTDeQPzp3IxFU4ux50zAtJAZCsTBVMxg7wOmWpPBJrHscXMNvzQjjDES9WEyHRJygRUqPJCLRlMz/gq/IpJtnM4zmDB2IcTeo+gohV3yOHgb1d4s/jKyiDB5MKaDEmvvMZo0OGs2+XmWcSztFjPKBP0xkWBnNeL6w7iQcKiyVK4PktcItkulFhT0OIX0ScWhA3AnPov0CJUUyOFyC+3kdwn+zyC/XU4Hx3ujM3QY4B9FqFsS6PG0SznSprqXU/4p3yivS8JlPyoN9NFEphrTOk4McWPz/7S8Ut8bOxAqpHoDtjwmNQ/aDc9m5nwH0Xr+tM1ioZ3tlpCl/bJjnjHfQcNT0DQ/kFHkco6JAOfS/0V7EFd7jEdohViOMKgFhMGNXkUaCp1KWbx8nteLRn1p8JBPPluiZ6zOJYl5MAb89aTp0usxOlf/7JViTagsGA5QrzFcxo5gsJlny9hYjMKq9TZl7+hdmSi+FWyYIIyFnYqtvCzPrJeNNjWlkyiTXXc15NzFbTMw+8P+7oOie4Gojyzj2dBCvRI1qxD/wEBb6FdnzFu4ORi15fg7jhPKaay08V+NNr4CMwy00QJjPfvo2qzMsNA7ZBoSPiXy7zTYZmIz4CyzQ0rrQDgCQ7DQkDfhOGfqbGE1sXXxa5vmUHDKiLYEJhI9qlEk4BPw/USktKl9MQU8YxjFjIVUOSOkiyk52E0d/Rja0BO1DyPRnq1UfBbDoUThdN1mNeScUOYelBnz0fQ8N4+A2/yzOc8lkacgl41Sy40rOHZDfFV9YYajk7wAKTkvHGEHlQsT2H/xFIC6ZnWdf6+HK+hK0e9nCmlKFMwc380PhMYbg7WuJsCRpbrPKGZ00i+H7NZ5njY6zthD5J6wukXUuM7bQ/X2OAbBFe2qTSHm5VeDg3H3Ya98hty69RrIsgVUEDlApOkb09iV/F3YBZmorbcw9b2TZ4mbfpZRdqsZVqJdVY6fKboSJLtzO3leKFhOcx5TeeYJN/9J1qyIsGQHttMNS8tKh3/Jc9e9v53DfmDEdO2k3N0TsCktH70hSmKjTe/+gmB4KgPRHsaZBkwsGcsOImQx5Tq+4sOqrQFXIafWdzGOnv7ll2LipLxt/a55XNE7egVGmHjDpz5a3tKbZYVKlJO9y7gFWOuiQhIpV5eZeU/XASpUGtBWGOigGgEvxyz0Vt+QPH6kcl62fGD5vc2gYZAae1u9u7QAlFfamS/Es5OBHudi2QwZ9rYrhKSaJzQwqPERadwI7dEG3us6ITRubCbpKHLvWFblJC73vG2/yIIuxaxjnKWeGcDWGP4T/7hIPa7urQHo6ywNL6Em8YqRl/kJ0zJ/cQ3EihYXihYwT7xCslJzSmykyMbdQ4/A/lPcGOWm7eRoIhLcmkXgdEd/WIL87fznuJ2GqOr+9KshVRP/rZTjAfS6MIRhnsfawUgweq5NML40UgO68dseHVETf7MhFqs7SFSjxdKENvxEGH+N6iJnyEKfv9Ul95RWChNgLpLmA9FaQ1jnQr99inxxWT+jsHaQrzuUaze8cgNOYIOrbZyJMr0ydo7mvzkI8HqxIWn1J1hXZQ7zTWbOqicbgVkq+jOC+co3zFi/llh++Cl36XpCnvNiXr8c4xthxYuWlk9lKrueweTEOcIdptScswVImlvcJGHJFUQ8eTWhVWgpE3ZzlytNUOV57DL0UKKIP1g+gyqz4aso2QZ6rtuNU7EuFu8laApUC5qJWgTDucqSVVRBJDY1ySkTfBhazz+7m6jjsJ8kZ7M7vVxA08qloh3M7mxE59lroO+IAnYnkdnRqzY4mQ3uT6rORRas/EHAoGTsmGBuk5aH+fkYcVzq1lxBGiojfL97kqZ6trvU3KFAwS9Mf4du2i3MabX41/aKusKA1MnxYI2EBZuKMPj0XwdSTRdrvpXfhMulGerryqjRQGwfkx79I+BoOEnCsjIqwq9UZLzgBAt0eWdBMdgZ7p32kdPu6O3BRyxTUQ81dD/SHSHXtXohOi0JxXHI4qaCDs6e6TWJxgMoaIJwodkGwlXCBQVYh68bpxQyZ4WBurX+xyYFxjSL9Rtc+ajiYz44cDLIuIGqOlBiiNK/McWo9qPE0TNce/ueDtyaKNe0Pea7Afhbt8uydC7Al0C6wXJPj7urvzhQ//3cwH+45F5iyT+Yr8Zk/+smQkscptFVvkGlkMW+PJ3FFHkOoyj4/zHtL+I9opLD/tVz6o9EkGK34qOqvf27qaNP0hfdN+NqYvfGY5RuIIXjBZ36cy4Lwp12Gu58cPxjiNHiFqciCBP3dPtDnIv3HIP3DWs40eWXU+3YUxYW9vAdUSDf2WUOBkGphGC25NfD2/CCrwyT40bZVsLFYMoUSFnXrXeyyCS/hI6pwOaPmSHeVsR7/QsKi+60Evdz5iULd+CO1TIyTToaVWLHhCDQajv8u3KH2aVC02nSchUeANc72d1zGEflK9djL9jSmJBEUIZo6LYiLBcGB5ySz4UKU145pdNgNoQRFoLIyHJ8bYi6oN+KhEy5OFgvU+5iUY+HJJUxMPPPRRZGmAbqwsUbNnO+LXeuki++bUlZsEURgkudo3V9GbQBAi9JbvFkIDze/5rjlC2ob8LUl3o9y4m+9lRiKWAzhhqiJ8JCa2LBLLp/Ldhp49g3BmiCKOd6adfnx5RhHJQQqYmL8unnegjCHn/s0/dshmIWMZKnWiZy5yQ24qK6QWdqhojTb1tY5BBM3fbsf7PxbzJRiLabB7+vCXbNnUSOnf0t8T5ZQe7uV+2MNXbJt5EsaOKtco/lUEUtU8eftWdYWF4K9Mvttvzg5AlXfwF4zA3CYv6txMDv7NBrWghJwPpC2pPuKfhUYdwLrFsu4gm08/Teohig48/3Nh8pkn9u8l9DbEL7aMaseN7ZvCpaC73koAgQIEWDLTglwrsOvDTTa76IKjZuJp339iTf0pVZXsmHONoiwC3goWe0uo7AAeDAMrAaHghYQJG2tGBEaIogICpO+uOxyuns5T5rhZvMjE7miDu/GukchEZfC/YXx7H4GQ1G3QUnEcFFEtgFtgZrMRrfYZ6heFiaz9q0Ev9EV51llKEp/XhHQyGmpV8jRwbB+BhOtymtm8dwYOzpnEl8SzNVPL1vnm/vnR9S353swOkbwk+GkBBr4kLwuv7AvBrw38An+MO26RM76UiplnxeQL0d2Yrzt97KEvzGEk8UFGpUqPAY3v49UWyxuFLa2simJZP/PLZvWG1td1Shcog5D9QCKS9UOUzPIIfOMCQYOJw1qDoUVx86wU3I9zqKKp3/vnGdQ1kdtoeON+OJdSkeEfiyzmu4vVQvjTCFdapRJ0l8NtyaskP2AVfJy3+nDrE5fbrH4IJMC3RCir4MBGCM7ANzOyjLh/eHa6TMhZGM700uCfrUEejdXAlpKMCgZp1NH43k5y3TM+R0wTbVkILCFOmzWItoBmWNYla/iD3L6wZ/sM2e65LZFf/XxBXUfrLFnn4OxZlw1YCGDlKw2zaJWMBJ+9pZNcvwVsuHrE1S6uOn0Sqlyoh14S+uGf+AiJdFKJ8etTpMFyf9B+jJHXEltXLT+mNKDHW0gy3ktVi2zXmz1RLzAqxvHRuAt/23mdtyGmN+xeAmaVYfjgs8Y+Ut6UyXDwKZaTRvURX1fZ0n41HRHGODf3kS72BaumuuFLt0JWYafuZl9FhzB7iTw4fWe0bA4gavQzysVWFESPeH4zEBM9hykjC+fNmfhYXrvpD8DMri918kqHQSNsZpx/vX4m6+qFs18bgIhz29bWL+HKCbRUQxK0wrD4Gp/Nd792j/BCN67YtnzRM8Z1fnSPM8A1x7VfNg+xLy2RGxNKf7fnyUqbzSnADpeRjZHvj9SoVwjQyobSsNuy5YcmMWfhfCDBXUZa5z/J9RgDYYePAtNOQdKoPRWwDlteJjHP1LK6SBNlSQrnTO5BeR6fMpQHXAkptgeF9LGpcvpzQxt0cyAhYRM30PuT5hRNp5w2kV3cTdxew3epXxsBq9JfX3ReFZyQNkGhvvgPR+W1w63UIRIOxfKsvwpW1W4UTldoFXblznVMWFU4VrIJCvVo+zAg4101O9i6qLV/EzXHrgMZoYcFgkFa1CCNtjPW00mCFWvCMQPcfrSU1PtPLu9r2yuMHuaPWx+7MFJd+bhlTtsGzwOcmwspvUYWbQfdPsCYGV0NZAL7DxUK7Yz7zeYVsxnpDjccKBVam7Z12Kx2iEaUAou057aFNd/uKW2h4IKaIrNuu6GgcMkpKXfzpwCXYt5kQMVqHPn293CX0V3qDHzXYBorsVVeo0JIHitJRiwn1nFT74V9PfU+aM5fSTWavvnLw1w0k9BxIYPN0OEzFpxFPYrARDRCXXzDNgZR0rVNRDXuIrSRfw8IGKlOzmzrVa4WMNSaAf0KupHChrVj9bkWh6zY53hUnL+E1sjDr5nzgslgYfeXdACZ4Y/0NEJpIT4suPXOm66+Ra5oHYd55ZI1kxf8GQRH2MML050MBSoRrgp6sDPGlI3wk9z2DS1fh+EC97Yl4yGN2valXMOmXRra8P7YAn2WsfjAiiy5haDHuJ/OfAWBi+J0POL217K62ouVmcFqa60CpuU0ynfsgPXZVixD6wNMNEHNeKQ5h8zOqMawUJc9hA7hWsIAtDoI85N9VorRwsAVVXiSijdKLzAxnpFJHY/K+FQRNfYS3dKlHGOdSEwrdxFcUxjwMCly7b6D/y0BICvycCuLYlCnRKxs29BqW81qQM35fewoHYCPXQ1eeNptHfflWzwHy6LbeKXeX4yZM+NsG7qZrNu8jFmEVJ2twICcfn26ADA1HkSS39O+aZ86cT1y0PvVYFt6VLFacQ8XeV7hO7n4tYjKRl6LXt9U3H+66TByL8A6yc0nhaqzpx1bydD0JNoc80NTiVUAGi3cl4FH0PHFKRbyrHc2pm9hP/UYUQPkTMZLUK/WPdI9PAA9PWA76RMcuJNW8bvYn5OlDSHf5LwlhaAUEUXCO8zTDnLA1Y+Rki0AUbeypOzUjfT8p2XTdpxSYBMgfKTgwF8Iffr7GvgYpLdLBrXiVHKlotW93KrkKiQyg+tiArXHqlMWiVaLEfFToIBmBXixs7dvuFF6MVrtjDqbfNe3B2GptOwUmsVLsWglDotv1pvzJN5s0ihaxb6Mr4Vu18g8clM9C4LOwzZMsXMk7iMQd8zaq3clv58AqAMJ7IhLJN8DeY5yAl/5sskgPjTZchjFv4L2zsYQ7e+yUHIX6S0bsfSmglTWljSIGxLvbjy+X9/IJavlbxfO2OLLtYGifBSJEZrnxqKeUt3ctJq0NjzirCnQXN7cVOFsT2PTF3dTmedLY+S9c8J1+a0j3TO2LyUxG5tVs7DQMFHvUHN33qxbxSXenxlorVoya9L3D2UTZi6VIkrZ7nAbdQJse8enwoaVK6xJBvEQYiGTxXiq9oE+oWf2yg32JoLr8WP9zbrrM+wXTEhhdLXxuU6o7eqJWuj0DwIoola2/kDcvzDv4RsYDFx5uAgoKITZ5cVPA+014vaB9YD4qUbNxa2kFgPiTLPjo1z50CYZYiL+7OgOLPi2unGNXLtIiEuF71psQfKu2vqpJwUpC8A8WOh0Oc1iw4cRWs6OSgD0+Q9yl6sigOUCZyawoRlVxorej6q8DXup+eBuEgdD475wbjKKv3vFYuf+hHls2WsScDqc3gTndh5RAWQEZzKKBelUyOno28R4D5KIqOh79eJvqON9TasURNpcdhhsXJZUf247c9dQmP4JgRPtXl5CoFgdHi3SQs7w0pIMP5J8sphwDXFQmHOx/Jxs9PxEem61O+4DdJ6VV/dfvItPDC/3QVoF3+5bV866XvqjGj8jbe9oVE1x3M9zgxDeeoq1UhcEIOzdZBNqPc4eqZTtxx9YyXp30IinYT38qIHDtGT825Nrt/x8PcrpTOEgOwh6tisEjpNuVtTyWs1yRhgAIL4MJJ1M0VKpj8WKZShPvxx/qv+MJh1D9dSAObN93OiNBJcjuf3X1ZOF5WSssuIzX1x3uCWmXHN0REry/SrwqAM1qS5+xSFm4xo08C6dyHiv5XVvi1JaCcGHM0Yb+kf4/H3qZXUQ5F9Abn0BotHvQ1aNuGYbwOJULw7bIZBePk7/koTwgQ6TmKv72Q4wASunfHIS4x41479yBCK7D661cyn00HCpoNkSiZOBXAkuDseqpAC77eZiFa1NBfWwHvnU4cSLlKpyG22GkuwJaouhfEDEVa92Yh/b669ZFsdh3565UUlBUadcLJS3uxfq3SRsc9YDML4mwMr88LxWcC8fJ77WsEblLwgiDUplKUn8GmSam60bws+VSjYOW9rS+qQMITzHuPIsqhrCHyknQrKGYE8X+dHMqBQPHfyNVC8LtYsuhZv5mUtFvlo7CLr55jCqpprDqllrWRCRX8ylE6pUdA+6Fhaxiet1nJ56tEZEmq70HsE+hOG+Yxulv7ezA4FnHZuPhQAVj618k7Uu3sugTcilvexVnzu+xwTL7oCB+yrJo4xDGQ/0wCwkTJPA/Rpr/akof5uB0AcFLIJ/IyYEyH4wAVaL+x3Wf80hhoiixuMZwkF+Rbu0O+tzsyyRhfG69sH/4q4E9iaHHGJHXbyBLBI+AVxgtmmtvUgLjTynCKZvTqx9+GRYTlxzmCatMFBtvhLXJYvjU1maq/AHa42wV9p/2rkEdaIked9NRUZ8zomh7gzNxr6THDLUo2PXcDJdZihCCEzBDgIoqw54/Xsm+U6xHTAA11XSNuWoLIkSqBa7lcvUnrWonO0bL5oc4zYKChksdYxz/7yBZhLsINmKoczkp1JYYNWPiqAIW6nR6tIFg5jNk+lX3cx7AWrcWQiTuvihwWPP/ZeRlzMTVx+9/qftSb36GFaKdacNx3RTt5OP8mlif+YAdeBgtRiKuuJxWd9BxJlLlSCbrTlkkea3rDBLU8BJDeNa+962AF8fP6aMUZLmXl2b2xzfvHGSpvxuh1FxUQup5xTfXPzvpIWKLDAbWJJWiWbUaT+JtHcfwMRjJ4KpkYdnGf3DS0jQ57gAGpaxF/8CwhjINVZ22hgO9v1f6HFhfxFAlnNzFzILCcwwKQ1GTXzrivbaop0afrHZn49kc1CbsHKD9V6KP35E2bdn9Hp+vkvrfmbbaNgRKdrkTx6HoalSCojZIS6LopBsIcpU1Vrmg3Dep09SSSKHjr60+oidPErYPbh8+lTI9lOSPBqf3plnBhhwB+gVgyy790l1FufgyuYlFl1nbkja3RkOA9ZoA65N//AOpDxe9SQv/wVip/PFmD2mGe/JDfWS/aHRbIGQruePXtlOWkR08Ji4VkW7gVr0G45136VizP81kkPy8WujC5EvyyX9RTeigc8+bLSBV3dpXSGPXAX8qxQFrOvwjWc+dI3Qknm0TGYM8Rext6zWrWPjUbMco4HnairKOO/3TcqoddnNtyFkGcQAwe/vebQvkZ4bgMPaMpYl9BctIciAcgV2aLZ+gLjK1RvuT367Ujusr/gLyLOteaHbx/Swqdv50SCIojsFebAXk5I8ndiCGltuq8Oh7sTRV5ibq7MJ1QcnNGmvfD407pyIreMhk5ucCY9tZIDJ6IUa6do1KkHcwcKRWQlgbdDv9eBFjTjgpS3BfED/Lp/EwGZuHb0Y5X4w+Lmv3VPlDhc0g+m5JXWrJJ/lNc93m1NTkSZDlpkXPwk7duc5E7qYWXPKR1QKufQhjSDGiWObuIHHVD9RW1y0p8rK5kEfNYvBhsq4VPnQTgrHOvyQrqr+5vlwE+G0CXd0U2W7o7/3XOJ8rMIcGHV6iMHON1ruANqdZoIA1MqBZDfvHnOfmsaj8OGUq6pOvsJnzh6ogNSTQnHMPEYLwcYZ+r1OFRyzOF2FLw7D2iKZfV33nzWi//f0TJKt4znEcWXKa+o6v68pa4DunuAlcB+0Ar/pjAt2hJcuurx8ARt4JaIK7nSaCNrZaTStHIzU08+DTFjy0fJQ1gkBUC7bl/ScU9CsZP4v0gTz53E37q5GCkwPtgDUoNvwbrS87noJYdw8sLd1/QjNEHj95i8jHStVtk9AI7Ofz7vl0DN1mZ513FMaxGeT3BRYXD8AspIVEcr6fIvn20bhf/VRKI2WgQqaqlxBdM/FO8E6AtC1BflPEcaB0LBlkG4NBEPdh/gYqUGFTUwQRDdLiUw3hy2tnAXt8/UmdeT5K1CR8PIhuoZdkBbTEAXw/T+/WOkGAHe3qpOhCJOFm0/aSAapuDsiK54InlS43GtKTC+g8SA00zAcOIXTHUbL2AtNeOM1zxV1Y5lw6eCGdBobllsgs/5QOLqe3xS7Zg1QmrSUB/amvXRVVZrle+6hJSvbbqAJhiuYq7o5Ohdno4aCYWrzXE2Babbm5ZDnG4L4enFDbodsqeJavUJY/dD0GyN0J8OkrUJE15sREtqeys6pJe9i3IVEtkVFkNxtSh3q5MYO8gZT6VG9ERXrUKhhCfTjADN5PtLhKs/7h/4eykbpzBMtZ5mCuqRhJxezwG6aJM38BXntCYH50oHac0I7iBEWxhqXsZtbiqWWCfBuZAJu6wPm+sZIpVgyONdIPZGBQznGTLdclQ/9FFCGzrUkboqYPqzJEnbOkXwAgFQtXL/gP9S0YQr66pGziC3aoMr7lUdQ0VgZiT+fQOKtXwT7oEP6JZO4PPMFWl3BVr4iO8gBMyTNq1Oh/Vq47WqPtRvQ/u9Oy3nRuAs8jKMkPqB4kduUh53QX2ibB87Rt6lUm4vcwhGYjxyALkerSDKyriPuShg0LTjw5a+NR0S/uA2wFy0Y+X+KjHiyADbpdgNW77P7tK8uKTSUnvMU/YWV0aFbiy4io8IBqJU73T+m2ZWAKX00XCqPqeGqtngO0s8U5/X65KafWAbrzmjzkdyo1BsC4Z8xpa3yo4e+tlNTe2bmfjkW2TY+omPabwkU1124k+Benbejzf0ADkkEuDwcDlkAYQT+w9aAj+Na5oXvcb7wuF9sDF3ixIrVO8/fKsQlW4ZX/2f7sS9zv8IeJHKEkDM5tgTVyw2JlRmggE2segraZm4i8wT5qLNkIp7bT1/+h8ZKo6U3JNDa2vCjMViumNWma69UQ0p/+QEBS4kjIsbDTZ27+oiOWHooDaW1kIhDbFhq+OpNybmbiTVAQCZl5FAJP2yQALduLX58dD3BYyl1JG70dwG3K4WCwEMhygRGMCrkpK3Bn8PDQGFOJIkKVxPyn9wiTlaugpQOEJoEgUqED15w/v16lRzkikO64g0JsRWFlpqIxGmJPjcM+rnzAuSmcTM/dnzl27ZRTpb1JYpqTUPT0ltCxeyNO0XplS/tkS1eN+mEHzeD4v+F9Hu5iBTee6ouIm1vryPM9pgp/m4EkryyPz80C7vqrnhNhQTTuW3L94qMN9z6f2dhW5qL1w+VMMF3IBrpmY4+6yi+MDLkUgNL6i7aNhG3OSOtJH98k2Se/n22gmrTtg7B0J+mdemcIW4Uj3Drn00IrbLHuFkKVyKNM+k/ogKUwJ2zBINT1R7eC3l4h++WG900eAH3rEk4grAkPqiFa6CCwQHWLD6PdDlC9rt0NvsijUcOGg+EnTq6RgCNrGuLqHBIzdXxCNuVooNJdULZPkzQua+maZMpnEigqAT/dhQWZuC4+y+ppCB3BlZHzfdjddBPUIzsRZP1YfzD/+rfuWWHyc6TNWkTPzBbDaVItruP6cbEIWrmKIX0n0EptPAmvipCbYJnbX26VrpINbtmwOa0AL1K9WO5L14IsyXHx2tr8WZiOGZzSTPbkFLgaEVJJISEx314+4ji1rqdxf8Td0BZc8lqYeSd/pySBavKfl/EYI0wTEAlV7+0BUpo9eS8PsBLNsruKsqKlyrhc5g1QKj7ITb9nplwLj7ZjxGqTiADl5q1+X+tn99RoLZ+/di6/Sd13o41lbzaY2B80b3JmqsgiVD+7xmFGKjfJL8ZfBMDhm2gHuWeY+jfLDJiSxXfRA7vxaPOsizn9y2pOvSkvgmPl8G8XlZficvLXL2kBJFeVVdKIpWn6Cs9lXDCwTG/XKKWJ2ENHRk2MemrwjZS5hU212sSL7e/XjOqv91kGSdHQnjn0HEfGC36TKrcaCIKe8kh04UHybA3GhACflJkwY48e6/pbq5dKZoc1zyWdRhNQtJ1vtpnm/szYQhwfKrAXxIvbbHGWnSsfUbvVu5BG+CNKidYtdzYVemKzqLiXvvDN2ZWbdGRShCf2GQYSCL+jn3QNOFjNpn2MWFOMJ14oExwT8S1RPa1DokiM2E5DHONPWjhRM37lMgXJeuNMgkzn2pOwKOlW85PbR9X2iCu4ta6kjxu2Xaj5NIA+z2MePiuNVJzid0qiDNEsrl7El7/uC4c0PncUw9YaazVz+iWrl0cMX/2SdxfZdAoKSqvEcshIxm6AWV/7XH6IR4nBerZhWm2iytoNvhy0vZNkLm5pVN7ZtXlXDiiRvkP1efNYq8/j6fUnNc4iXro3k0TkQ/Cu58+jcLeXtu9f57fCXm69iu9qyk/vRvw6/D2K0aAeMUEslMsx749EhQoXlkGwuRh8nK3jEsilPgJu2omR2kM43F3WBqd4zEvRb2uxS9GSTPLrSka1HkDNduF6NDEA/NoRxuBZXDEqylxVOz7nrfEQo4rV2piCtZRRS85RqLLc6Y5IgQIQ39qJNWl2FU0U2SZWR6bQmh6P5nMQFEg9QRskU1qgWRYLkRE/lB+kGyZc0m/i/UAn51j8F0h/6q7HEybRiHQEJFR9dtTUc0IZMRTPznBK9sKxuUz77v+yR8wX0iCXx5M2TjbxZuokdmWMBwMuXUpqmA1Rw2EA9lbnUtAU6KKNBK1zk+gq74XleNt+F8NGuLXbDea7hHydQkpzilzr4yUGKomSqQ8PWJQheh6QTY+GJTs3aMhoE/8qDaouoWhzFx0jbQ+AweV9zupUl94n2kF/1K/hD+eI71cRC9GGnuockSqcLKamSJwMwrO2NpYuUYhRxIrYtu749YRsV6TNRIvrYw83vvbr+v0ABWxEv52gwWTtH11aGKNkWQQ1b14/xjo2HVYvBSF5CtfLGimpKGgnOOoydAzv0SrsBixxRRxdjJFad4GrbVFX1AUs/Aan6MGTN+tEwNwwA4Aut+3v2YCzkP02IAQxBdrCl8CMaNCxDp22X9xEeF5Y1x219n7/qdJJ3stGfNHUvBj3Ob/nWXGtFmTeOF62nXi0Gz67YaXWMlZm2YYtAXxFD6xPn/VNbZQf/VcklQHGGJ97+4jvi5mBHA8Fd9p9sMdScGXHzOipLz3xcqPCwvDZG00lboiLn+C1LT+ww1Y8IiRYuJhb7IYzNCP+1tlmqeWpUYZQF8IsMpr23LQcLHWsy74N3eDtEB4Zzh7TlLatUnESmbsPIOiTKzwcSNtrEak492Zg2zwuIo27eWkwr7zv36saSYKCCqH2wm5v/WNYbfwHuo6LtlHYTZTG5+rIJZAbtz0C9ug8yqJIcJtUM7wT9zdYHRzaI2ha4R3PE4/TDwmGRLVT+RlEtmwlkzOsOToeSHpImYpLcmt8OW1FRa7YtdcctjAmwCNwKWzyRnmI3pTgkMD0lQcQTtFGXfCzVl7RZLhWCkYcb69xnkINTBN8MHfUb/E0dRSSCSCHuJB0HtTwwz+HQkb2dkRSxQu4KYY0Fnsf39RKdP4XtZjU67svqQmOStIF+3Fe80TwBK4Sd/4iwCKcUr/gaO/SzT4qqTlgQnZ0fzhLPku1Z6x1rx8+RysLAz8GktZRpaZREpPy45JK1jpKDkPfpK7QgZtqSXXod1XymL2DGLjP6Rff9hSktWoyfOf0LLl5Ul32HCjA9kp29TdFPewqhfM1qF0iXU3Jj3LxAm/53aIIM2FS1OmIsFs/KXuIO3T5OShT8n3F7SDvhFtHkGcySHqx/ob3LEOfqK0Hk9fJbndilXetElJTr8eUaTf+uLnzF+Budahjx1Iqhcyj9yYox1cBfM7QucIh3+TLjxtsvgg8vS+H7qunp/GW99v1+IP0kd9asRthoGubb3hxGstaaulQ7kEFTgIENpgtd/Od9X3YIuYY+dTQR1u3x/CDd0Qb6wln635jxR8izXwPgSCXL1r64goH1Sn9MnA2eitmYmkmm+CdPAIDBZCLzCyWJt3U7NvwYjhjaLOQaS9uE2OYDKdbRcj4TFnrvxJW02ytXW/ZKuB9hj7QWm9VU7Tt5nXjaDgShOvFe7JvhE6W9YKenLpQaMzDL0orff28dny2ermSqwd/igF8ddafu4/VjMZrXySi4TwMwY2JRpE1Ht9CiJwwYN0CblhZ4ST812L+YBZg4xZM2WjWaM0gfRehFKAqk5dM4yCqRr3kBXjfXjcM2K6BPmhxCmqpD4wzOd35/75eKBEoYqKfyVamK7yn5ZqUO2P6Lh/bVpStGyDJ7u9zuL/RwW2v5/bpGvfVCEA58vIu4//Ax48S848JjBrhwlgS+XJ80lXmg9Luz3wLfF1RsAkDR1YjxddJx3Oyl7P3Qw5TkQwA5PxsfDKbEoFVIOtAJD7aaE0Q0nNmdqp1+ZgwYN0a1IyZkFOapC13u1ecF+tzT4oxHaa233c3oDwdJaWSv/2tcGkFGkuZM1vEVZM4LudLC7tUY1DMsZf4hqFU1G7STYuLB59DjGHrNa2HG0Wc7QphWcHi/pyHnYVu1Z4SnAO0dDjLNe6r5l/byIaO/0KSBePd/kuNtGL7zbvI3fK8NVa9OlSpkTFtDS1q/pz98UqY7X1rYUnAW5IOr4rDooTqwZARPftCxRFEJFfLaxGCUYqTR7yWCA+Z8SVchUQ3KX4m6K2EJa8QkMTovLgli0baPKmSua1zxM55DkCN5mrMQBHg9KfLyU9kRWCTEG+b6w5TQF5fyfR/IQqG/8u9UZin27JzmxOd8hqj2SKOfIwgpIsUToCAMFKzJ7WbBNJcAxyMJ/p0CBYpYhpJ+9MJAQAf+rRWynybhN2hOgY7Rw5F2NSWr477ljZHlcqBmsTA2rGx0f21wkr2xKSl36Q15c6U3dhlLjei56Z1227Q138SiBdEkDFis3rK6QhsiqbcCba3AepzZ2CgN55DDRajt3Lv6CZffwCDwggbHy62RXn0MJXDblLwo7dcHa26q/tPBX30eV/flrzw6BWAic8d2cxua0PH9a18UFCoM1ZOsNHC4kCZE/0J9jdLa44JWPXTueKUlK2iDZmfTKptkP+AzUaVunH9QBDe61jVGe+3U7Utp7TniGZsDKgnawTvdFh1S7YPXiJB8P+hghjuayG05yelwH3vpBIBiM/xL5ivii6Wdp6gF7GZ48CUZfhvLdg5hyOvU+E4qUSlH2OWlmZV0514osSnB++b4n+t5c5mJZLrysaVAKHSNyG6bTQcPGmzadrUfkr/wDjM46e7UFjkGM2GaXwBjeP75iAyiq1FBDEy4A/4hd7wZnfA9mCc+mwS/Iq2nTK4kjwXqjqQuOD5iYZhiUZOPb6UYYZd9GunZzoDQQS/3syx/Hzg7yAKGoSwgQ6Hz1QXgurUdHabbcUKQxHQftO8t7DC/e+gnGdLDq5an+GzWY+mcp8rJNvXy8qI77NJ1FY0S7RUHeoFsebbyp6L5sdfJIMLqVMBcnAO0e2fkCSbfiFociXzpu8OaauAZvKaAAtuqpg9RlyoJO3e2RDC3YHecC2UTsWclVZxJjZGazM2gHbN8EXzJFX/aGd8Mwy3EEPSeVgMUJpcVvAJNjI+HV3Zk9HhjJ+ksLsmQ5xQUBJBXU2+4HFhPCYjmmEKRYGjotHjXbU34NzR3DEbIUzgPsUpb/S292EPwax+f7YmxnB4utlSxKCaqBfJCAOv89TmPKSiR5u4Lf5WaJG4EdLZ3jVNUVcqq9CEAMja7DfyWuypL76MHK5SXoymaTztMCua2UZ8Bk8bJPlV32n/y7OlZEJeqnTrc24EX8tpn024x08fOEe7X2At1ym8LHwQMIRk6Bp2ryOqPkhcrpSFw+0RqM3hlxVWVK5CLqSMqrTk/6DWwmrNMWlZbIERDZH7IZnq4Sy1xBN4IhgxtVESjJSlQEy16GKdEpX2iKbgD2Spnso+gpJrh5tnWgtSQSwByJ6juJ2DLZFM1yJNnAkBXJ2u+0jHvy2+azIAPSZyroKqGQSEe7AUWV0k6eBNpyizR8AeqbNjZpd3UOAl3+43+eaN1lbW5/Y1j86tdrOWsUCVsbz6At5Y1O9VqoDleTX9kJB44Il1ALEaFnVY/uWW1BWOJ0Dziacm6Ks0i/lrE4Xmtzw2ij38q9c6o5YC0iMnbcOb86Dj5hn1sZMHzzPpN4KEE2yw7ybSWzR4Yp8O4jumcfGK4flXMwmOUDqYRmHpV32d50l2AwWoH0Oxyy7zG2syHsYv7iBNw+Ny31xcZi/U5WfHhnsvlbNDl+SvwP76I+1+mrjl2GMCIRc/3Xr5H8W/AtMPVfTNIfuhwKw2XgsjmYFvieykvlPTAgMJXk7wZRPmoqgAoEwCXPV2WATWHQEjfgJsxlWTD+/4JTbHUDSvzfYcwm2xdt+SUStJwTpc4xC7mlFbhT3DnUaNR6aDme/AvOb0xlWYBWpjVoHFHM9MiclWOwI+WHuwhzVhrHFRBjQ62iFM5MUwFSi2wb7Xb8u12SFw37uHV+Aflbc45q8qGy2tB9PchTwIhAUuUzPU4wJ87q4AQs7naKg1sEaSLUYoRoatuVMkeDxOzeqmfgeLX3NR3f0H6YKMgjnYa8rdiaUh4en6wQI6lg6Oq/XdLfTCUBNhPZRoKGYgnjTlEVOWEQ9zV9vbPnncaydWyUMVr1C67TJvb5Uy1Sc9r93v0Lm3TE9sm7By6OqW3WNetkWghVrNregK7+bx7yByLjvXv01Wyq8w6J7crqsgueGaZj9XZRK7lijAH6FSQlNmeZC9NxgM8XAFsAHrp7LlpgD545zF09fgoyQwv3NpsBGUcjCjm8yRJoBobxN5XDDcxBkkUhfkoNiJj4t1IuBj4CruuYBLHQc4n8lvZh6wzMowhj+wbCogF4L+Xas7Lbee3E4hWFqRvpq9yitaZ5O8e2vUT9QVvEdCf6BDp6HyV5DcPxMQiGpASwlqgemHZP+5Ulm7KM1k/UWAFbffkUpN+l4XpBdQ3V2MQCg8xWS/0u8BZWLd1dLuONM39moeDQXmX6QSv+hT+OkQ5ouyCEC+Gt+0IDK2c7EfqAH9Elgo/qfxrhXkPPz2wWoWraATqUdGDeYA9/crX2ixN8xsveU5sTvQVYqAQhFhmRoBZEZ41/ToVgNDfLFZvu5AYHVadqrIpSMXyWl3Suto1cTxAXwJbWOeuwf5vTkPgJ6zoqjdOZKvYrcHdolmvg6ZGiyw3cj/3zkjLo9eWMPNAZInvRP61tqWGtPRcp1u3w9QFdEfSv+lCKuXzWTZ7S8imhPKdOwqdjtgzHEZEF3tATjmjlMpqWWaPDJce2kq4sa6/NMxXQzoVXu19rJZ3e8xhnkOaWYgI/eDZ+8WF0ATcL/qNqgtWsDZppwxETK7hfkwdW+Hae2Wxfl4KSm/I2nCZj6KcGvy84NmmkNwZiHjP7VE4h+yfe6zmK2HFIvSfKUame99RD7T7YNB1bv+DGWbc8AhiMH8p0ZAzYTA9CXUEZCwEMZeBRwsbNo1YgGAponTppjEnILUye/vsyhdVzmBZPo2UgTI/Xs+0CW8ZDbZ5p2FgALbqCWlfWVO91N0/w2qlGp4Lyo3D6d9tgrtRmnRJ6PVGrB7WwmVZ4uUgznEY2SJoAgaKUV+re7XuN96zbeKHw1SQeKY1/v105ImR8Xi8rCpmUnN+mX4cHCHeF+VnoM7GbtF+6IJ7s+HuWce2TIQIdU6+UGpkCgFY38caPVRtZ2dbdU1HhU3Jfb6E7NJrRIfbj6kr5Dk9r1xQag+bD/C/Sz0iObzYlza7xHoEKt+afJ2v//lURg0qi9rs6U9c8HUU9SeXfY2a2uTXOtG1Scr0pbUtdnBE1FY+aMk9Dwy2Y8PiCI2dwAyZ97BLrBCqXx3hB+vWMi+WOV1u6/esZw4gs4hbtSxYFXQ5wA+49u/Ovq8qOy0w0ycfYOWVUYx6NRYb8ba1SpuKk4N3C7F/NTw51stGO+ieZgOS64OL442mhT6FjPdEgMq96LusGxD2XFzEQ63y0I6uZSL2yRPGYD3qHKfSk+l+sfYsNBWZH/C3dlt9k4L+rqjaXzs1VqsadZqIG0nz2PZPfJIfsvu/uOtoYQv5IzFt9KADl28nOzr6LOvcdy+74+3RJgUIUxHrLkjLM66ahukYiYbMxx69xC8f9bZlqTNtbGkKAfSyuYI+sYHzGKrxWeVloxtI1fkcuv66NRvJKsEwOmMqU6mfhCxJjDsdAk+oJ2d/E5qyPyLYzTmdqybb5SNzpIz+mZU1MuSZDGxErBmFLFvjhLvzukY+4YJPIxdV+ek7hx0UWVwm81zOahxOy8cqC2a3Owt7Hpu84Y41KqeTNyxNCgX2HVJaz/gose/0KeRBOsTKJWSHVm9pqOifAFsAbJZCM4RNRoubV7lFWiMXMendaaykFNR8jsAFOVTSH18E0A0pDVc5VA2X6kOIYPd57fIwwH3MwHTT3UsXvX4eXju/oRT1HVTyav9s/YaIXnVREeAdGr8NocuHDbL44yyW/Dm55yXXo/debx8qgHbTTaj6qMRb9Yrpadk0awyn/+pgwteM4tEPDLHXQrWuNuJNupPNgTSiKfKiAYVYzsfU1iHug94oQOejW5yOYPQ4+eEulwwjBusEZyU4Rg+I+p2oybMQfWIwyoZJMaFxBc0Jj85ssEC2XHcMuBRaLfLUq6kOusl5dQJfTkQZxqA61/rEh5qKJaeo8gEU6lygi3VXve84Ooddmbr4tXEEZBiSrb/w6I1nRy9cjkxtxE6c+WCrFhm0JhTTIsd/dUHhDyCOjbHECWFYm7V1GjGaebmSmR9ChfvQmE7nCVivk6uNWHOuPFJwDKcpMQ1oUD8Oa0FCkIY/FQ/VRrfGnezV2LoR1p+04KxsXqo2HDsZOoHamSAzMfHO5cGUdlsjx19G6z4ri3G0d8bftr5Rei5tWUTOa/moBGb5Fj2s/rLYkby1tknmM6Ma9sV8OAhJNVjw190JqjQTcuYwKma25UFjO9Vjez6eu0lzSJ5VTBcvp0RlBs734KHUkm2Y92B6oCZ3uMD+QLPmalMddDE0Y+a24N1wLooHiB0kKcEIKB2Api/ec8aG7gmQmUJgyAgMFKmbtqad8YflDeRdT31DXgJqzQmg78ch0TaUiHdIfv0yE8Ip/65YmBAORdLCZ6wPL6cMU9EPt6wvcNFHs7GazKCLdqQG1z7Bmj/XdxrjCvdVt0hD2Th44k+5JyUaaD1XpTTzhYxnbWzVNiMZV4C/JjCE4294d/QxsCReQdyLCz3Gpq3dMK+FO55HCWpaPQGYWC41K1iKtU1GJ92BLzTeN4ow8DFRtwrEbNdwGIQLDqNah46ONdatLEdg+aCcF3Ee9o74InlimyjJPGlCHTHXOKP6770z+5ZP6QYBuvo1sTPbK7utYGZczYU/BfHV1thfzeJNUW/4r8OONDC6ElOn+bxykg5xIeHlEkVd8aML1FE0ODjn5CDV5BUaIP8b18JStGOLTqB93KZcA61ktdlrs4XCxfZ9c0tgIgzzlOcixV7BOUSu5YuES3HiioUNaZsFUVcO5VhyRL8zq6PQJNnq1DusYYn0SlwZlXLxlX+M2BCXidV0e+4hDbYFR2x3Y8E/tqm9wl7J1atlqZrSHM/SnOJirPEc18Mp23Amw/r88zTIZDUtp6gYHoba0CUaTPeG9ag1FgAquIGAzQe/sfhMRNSUlXYwfG61DmEKiocwz9TYXOAHxXhuFnDCKXm+hnarHDkS2rXSKki8Op0HzJZU4Lsq29769VmdDbg2UTgTlDFBcXaKhL18ubmprfGFn2YGW9GVRYoDdbmOz85EYifMb5mGq2XZCnN6cToCdRJYnb9tNCG+GLA/JmOw6ZdP2+nOUrMKt1/EfaK+61XuS6A06CTzkez6nvjYVignRZ9GuxjWOmgpsxrI3CfvsHm+icxx3+fOTuIqt9otxieaAjlbEI5gf5hAZR67w7/GeZV0qPcpMl0OsnIA0ReOOEouE5rlMzE8i3Vo9VwkrMKjPfLdPHs0Th/ZSQR5KlDU4ES0WynfbAsswVCQ/DGHmeePZbRKfuxFGqlose2nvqyhWVml1AHnSMNqB0Ug15h7bPeeEkbcHbYUbmbMfOqsEmLoUjLr5ZsTECybq2G0XCPGaU0nhq3dCSyWvxdueCkcGwQvoAmUP5wFwiY91n8aNNqagr2RmH+WM1LxfCJiNSzsE06GloXHtsoNjtgqKMQreUnoXn2pZkpMSm5V7l0P/a1l/HYP+gK9BxLhwJyC//AL87rqV8rFc9d8T4JpzCDZxpJ5oKu700zgellgdzVe812BNh0FxPvy99iLnLlUOgfAJXPfgSZo7G69LrSEBZkOp7JG8GXPQEmQKnUJRWCOhmvnEeYxAwjS831wucU93Tv2Y3FUiSRgfdphnul/a8FTTUMfbW7pZ9TX+Xy1B+0gRNSPNZtUJFfz4SatZqzKVsJPnc/dm6L0J9uT5SbVyP/9XVXJilmF1Ki2qvkXzRGVubrmTCFdiHOt6xwdYCWYy49qyKTpiY5ytW3vQiQLMCjoDJykQuYsV9Ta5tzbTDWLyhmx2QjqeSQNEakldihosNvroJQh4dnhgShYL0+tK6D9to/kfR8ShluaHd4efWTfhIxEyRasnWzEgtyDQo3SnSCKeDko3gj6++HpVzNxdXA+mDrZ0nndophTIG3QL5NnT3VwPSD/1QmSeaadxfZ9OgbC3AmT6ycS1MNsaaUqLn/ASc0F8OJPXOJSuEMsd3CsZxInMlvLtm8w4Vxj1XOBPoz5nMm1r5hDMTo9iFPfvktnQSAv33OBItSJ8Q9R2tQf9MUmXOvpyo0lzAkFqpRL4g7F0+UrYrMLRYWodRvzXETcRPSBDZH7kKzhTNFqVuNIrr7EhLWIGeEdCn3cnHezP58tcoHUYIiQTBvub+Xy9X2VzntM+M9y9N9syHmbTOowO5pbONs3jboWuhx+xaTU3mdXq6MQ8dqMM6zGMQwAqjVk/YltrEVEX7SbkQuM9iRgoI4Iuooj8W7gwT++Y527UTOSSSI8kTF1JZcis+h1GOOSf0iikgVF9e0nGarM/9mYlQBp/Th50MH/djZYbRYs5TMsxv08+G/+0yYCNS/pq2+PpSBr563YGBXQKYTx/o55zdTvqXXpHa+A/sT/pDkKPFIO4YG5E2qaMaBwc3SuGBEa2/0Ra/ovINfpMTVVGnmVc0HCDQXxfWH4f/AXoUcnx3vBS/9seBzuZZE7PtZeDxRghMo12hIRegaRQkRAwEUf0c2voAOvo2Vvl64BEbgUVqQ96JyLJ+orW7M+8bKrvVCMllm2NE34sRTf5ZUcHAu743mg7bZp5pRRM8sO8ehGrNjTeGlXus3QLFIvls/6hfToQJZaPPAs4FVzeFS1xfUxKDhkkJhgkyBScjlvEPIQyaPd4i6++gPHLxGiA/pLupUQ+kDjymWMLzYpgdaBjCDqfA34Ub2opmG52c2Hb+LDN0Ha7VsdTA+sbSEjxXgixWWD6Cpk31XpONdy56iwO9x1KAWH4E6x50MMMXAeaa76f40pXwTPaeXjrCaqC0s82rycBv6TabARBZB1JFb2FbWzOBENmJh5iB4sI6sPPcSr3lCJLQL31iS/sNJrSB9/dTJEI80NiN5sXlOCDVNvy+qmakrL5mAriCqZutJZOi3Vv9bwSOO/cSqyN+Zw72luXT9Q0Re46zFSVGVTnyljBIRnBwAYtQgqHZkmTgZI/ZYePbeiNBdkZL0nmIf071VYwkPS4+0Bmk4JAWK4HtyVsFVdhe2xy/fQlU9TdAaNozQ3WebUqtHe4DSS/WNxjrqW58NkmJlo5t0z4oKpjRbFeIuw2p+W7mDl67ks7Dam46+luhN7T1/Yrc667k6Q4M0kuB98oNpAXlnJyBhpqpFCb6umTEc1LQqIs2C4NgY+Bh/Yl4aZOhzAkSZG0skrbiHAi4+ex2f1sOxvnegMVfEtDRaf6g9/WmyhkhpNt1qiX0x5l5AkbY4SNTBnVMw1e28QGof3qBIPZ0WkE68EKQmDWoNylc2Qwe6Np8Cgt4OxhxtTXmL4Eiq3Sdx4knaNOBYK2jUU8zy4CqTp2IvS8jKUlochhfyM9X+r+dRkZ78TcpUljVy2Jjiel/9NtIotOuEpnRTg2aOtl3J83yqSPyvcx5UnWc6rfdmebgNHoGTkD5koVH9h7AEE7ulQr/VQ8Pbuo5mlVc+mahaeTDL6fDnWBn0tHGM9OW2ZTpGEbpEdAtE3Q5gQ5HdFgOQLMMggPy7kTXdVgyJd9HXlhSjvlwoDMXZ9Pv/tvopIbZbBxqu7NwNJhQic1pAZS3txGDJdPz3V7jMR9iChzsB0r0BjCL91T5DoXVu2PhXmKHgoRgNeHZlOINDr0vGQ16nzv4ycOeDjAOss784JNFK1tiQacl+SnOZbQTMAlBUVBM7ILByFynHWeaQ22CY1idT4ia5YBIGFxJIVSEIEV3uaWhHAb1i/uKgWncKNvS42WUQTsyx+zVZPRn0Qh6755iJkwFuksqxvbdltVCp+okveywwp6TIQFuaNxlDHgsWiOvhzYvpgXGU6DQydmIAV4QCiHXbQpCxG8u53a5bWsMnOXSjV2Ut3VSDydySC5dr/UgXEqc3F3fqn9dLilWbHGsC/9hjfO+aowgrr3m01U3bxG7nrdSG33BHhRXhYB59JoPyTcqpyR+AWJw17qiN8L6yXBnvzkEC/fLkhxlZFXRXoUAJ2XFjjyFW/Ng2LpWAcNXV7JAgbN4QpkoIvQZH3UyuhwJxBDochVTsbivs3Rq5AH6Et0CD0ZajcMmT4wVv5zSWG4znTtcHbijLlAknQoNss0OQpruKF6OHDOKUanUKtHVc3vTfAkSAT6q/qC5ythkZhdPIDgIKh0i7vlnNehpUagdyu551WYXun1FLMN7qWHKZ4vqDFp2XrDxVpLXkk9Mlam1bkiNxRwBMLGwU6Mjx3plQ2FeZYW4NSr4evShAHbpLhJgKfzsJMojLHZgHo4H3cKRM9ifaqm/K934rVxjJBi+cN4WNY/6yDee32Q/rSO3IOTFbPEIHHirubBRAMt8R6CMzQat6MvXYSUk2h4lSBliqEVbAnPEFB4OprSIp6mu90kArs/u+jpEfGMAq78cO1+o6P80oPrxfXpVF+vkukSv5FChgtF/1ItCBgK0ZzgTXO35C2hiQ44z87UeDNpqklAAWVywRhLiOQAl0YCE0Ba2yT8XrLFwKcazB9O+vd8W/PnZmTB9inBSiYZS8aHC+sw89Ecp16CJsG+U6An4KOuqlokWfXRUQa7tUwLyDNMYw2y6nFR3hUDCMn4kK8/e/uhuxPSGR1cwmQYRPmUIEgbOrGSbAq+ytLRUofhqyDGpJ5ffi/Jo+mlLAzt/OjCfZ6cprJp7uQNQdKTmR0bb7tRxL6DAVzKPItsoidrVGq0arljpCO9eo7O44aCU64XUpRZPgtMaMrEHFYnNcORgmxY7lvPNsOxVbxkhZU+DikKnCEC7LH8dHyAESfr2RbEPjWTBtrK80bKj9PYo+v+KQfos4ru25EdbV+5heZ+jgqi8IU80aCoWtFS5NDM+G80zP8Bp0k/SwwXudQfsgv7d9VlP6aCJhiDiFFad/JVT3I5SxrkFnh3UNx/TvRRVJT2glPnvCC3LqmzM3AFfN6xGu3uNQMHnLsAs7uPSswwI04aw6CPH/QFhT6EVpbZWtk0rscNECvZE1+UubE+4ZYm65QArN2wpgZjOwb6xGCKFl6AdePNJjS3L8z8vgNkuIQsaU2Lmx1+TuthsrCv3Ry9u2JgW9sAw02MDCrtJSz1uBh2LeU361b7AyM/RrA9EBe4MklmOMiSXu8JyoVxnIK8vIx5Mrw6Ysv+xyhyK6niyl+VpXa7lt2i+kqUpo7vj7O7yGohTgdKs2onP9fmoqgGkDipLIHHBP46z/O+KTPQhAcpXX/J9cgQtdDZPEYgqmfuF3fkJck07o1+yEvKOC7Jboxp0BZl679eS1Hyt17H/t7EoUMkP0xtcD49V7Js+nDyXi/aUBK++jni19uXMGYXL8SNODa0N9VuASr3rWQp2i8TM02TJc55u7/PIL6vmIzezTGonYP6LY55/e/aXtUWbgS9yO+OyI4c8nrweRgG1oUCusD+4QwDzYVMvPdDvI7+T8cZbgWCaVf2+xgAyvx7DQ8Edp8h4GuKkLUa046YKU+HGbz4KtswbZRnx9Rag0IwWKZIc3B8jcPmzjx4t8c4xguJh82Kgs5JdFQLFO3pj6zAN3YtAfSyflPyjWGK/4+k7r6NtvtwyHWTtR1ylBweewzUqrLMSyKwH8zGUZr94z8dfNI5b6XQ32Wul0OCxSCZQfVJjWtQO5BwXxXRSFx4tGfrMjeK2C41sB0IZWnoDmsV8szcikOCCljV/cl5R1zPhIg+Ci500WYZieI2mY6aPAEe2OVCBph/K36PwwdT3ZCR+T5ZUlyUVT78IqOjYKBOxMSuUSmDUnpihVeaFt9tjCqVruMTSsed4598de91/40JSl1kiMhNKjAaCycIUfKb4YEvSbMfp75Cy0O9/iHp3lzxiCvbsMDBZPADs7RsoE0k8KNv4lRojTtHy3rvqppFBzYS6z14T05CsbYSBiNbata7d4SZew7TnOWcitLdb1I3ex4+l7qcGet78COUtq0FthbPXnkXAgejP3FaOlHuG6477Jb41Wcrg9+gLDpgPTscabbBEGxGZsRN5Cvf+b5z7KiXC6MDVbjZeRcd4XjWIswuK+lW4vYw4aIx42cE5KI3KDICHpJiHPq+jTF5G0szNcWeHMfOUkUhTlyvVTMfY0kGL6SqbfInPZtuTb4q/tqaRhTa0Z5MjY0AxHKFdHW40k7/Hcp0guq8hUB2sYm7y5EB95Ej1lTD34TZPyFk/CHFynXaZVI5R5W2S4X71FTsTAyTLcNjkMXU//vHDHaZWyKTWM5oKjwL/aSO5NdQs+W8m7WPusvU1WHJY1Bpp7XearYN9iSiZHeaV/CAu2j88gU0CWmCwJcxHxbLpuddar7suhSWLSHirjBrQHJ93+bFD4qncnoKjXgwW3tshckQ5FPvWb8mlMzLz+JLdh7tkyBBe3bmuai8IMPyxWBcjS+dZdopuE0xgblisIh4mLtSJN+JLWtt5RhdOhGCLK8whOlxKsZ9gWh0qccUjTt47TIZSujbQz7kSTT23aNnoshHTFw35Up4M8UVkjVFpMx7oY09JHamwOQT5fme/G5+am1q1qluJicQd4+wCfylHrO0kkdIUJ1qVNUI3/lGfEgl4rtmuhfLdFInNCQ1G21aLF3yQX2ItlzyzlxAR8NvSOGON0oqDOAM5IJH0dV+9yaS76cf77PHep3QhiNExh+jcsmdjBBc/K5EDiSZyqP3OdBEUNrweVexd4pgvA1hsCHRANzK8mvJ5Caac4QAPrDxNIWtj6phQLzYUQaA5WkU0AEggaTjirroggeNZJT+5jVl/iGUerBZgdUXybYmuWcEnLbWUr/gxvE7NGjjIwBrvua+wCq1YTaa6Ayjsv6T+u4IGUJJtJGWbjHy54sIElOdqxW/VDNqlT4DsT1KdW8HW+4E489FvMoGAGj8mnW+BHbvkpLhneesKgxBY4PqtoeK5VzOQ360yttBjF7O0rgqpyzPsNFv1Coly23NZXpd0vZT00YqSJajxY7qPFB4X4i7J8Rlll4TlRpymB07qZSjWQIaMD9CN2MzLMIdPfDNRYqpMQkOF85Iirf+xIfW715/keT6w4HyXFiKIICA7RsIZAzYe7uSBTRIWkM7qqBrltB4RE9euEakNsGzMBSeGyPBGVz1nZl6MWnYTce8pyvsK0xKTkkvZMsRNcP/HJYwm4qVsKIoizSj1B7xj150gOr0grKaS/nEUvl1CoAj9YcYOOu4OXUJU0CKbQlO/fbN3bazzqcrzeLgYz/9QvNQAmJgZhqBRV5d3lB47ZH/8x3rNOalc74t6ugO+0bESogdOsk5voXb9Dti3DFwRxlQ+rT4rxd++kxk4p/AwgBpPzFhQekCpG4T69JTIlOIimN75kx3BOSVpugQFAMLjFS0HqTvWI2NOgnkD+WWo4Nf1CNj9fhOTGCnlZvfpt3cgBLV3E8Iak4auKHIN4kbiC3aW45LlcTd56vLPhbKomIq6VnpEJpcqXTCIuleE99mdEv9MC7YD8bewMnzVY2peSVMFrKvvOP/q4LxmYOljf/dYMOW2Jw6NMnc+AyqcZBi56HktJleNtlLVbRON06+Ir7NNYbsfsxmGABB7CT5vBgd2mlhfl8+bwhU8DaxxZAwhK0oZh1EfAQhGd2xTg/YQxAjb2KTwexXhHCPOs+DMJDxmiGjWiUug+QEEqb9y/wxH20PjEbWbNbAL59In+m6pB9GeJraR6IWTiPoW4WYwNOAoPnegHA5iU3wH8t7hhjYjtn+KZjetsVKQgeDzB8lYNUKUnIz7q/BSfNs5qgmc1c+mE6ZFa2K2449TxqrMe2DFu3OrccbBEV27knEULwGAwZdZPlz+YM0NnALDkcMfYBIN0jW34f6sYY/kF/w1OBxdVYGe5NaXWOrnn3b8uvm9tJ9isV1Av5c3AmOkF4VAm7i93IvCz7+7I58vGswoapQ+7dYz3rSobpvn22xlTcd5AQi6qJ3QwiSV+/EDe6aaGINXDFoKJZUkHGPunbjWbw9GjrnIYVoQZs96Wmt/TpP2MwrS4K15gRHsSPa4NSRrT/jXewF2mEq3wnKI9dmeZhkb49CfgpMpryEh1UIHmDTV7Gh1h9d7g22abCCzmSjBtRXa6jaVQXO0qJupf2BA6d1WRtlRenaUeaKYWKek3IvHFK2F/F479kGQFYkA8wietjg1ZQ274RgWLkXoEzsbJmbIne2ld3QnIM9Ujr1s2lWmZuWQohtQMhkpWp9Jo5dy7tHeRClFurnw8bEKgLG8YCko9XBgR0w28Jf4VhiuhD/kV6rlluCYcT9KOn5EmhcymYAJOrsNmod/QFnmbIzqaR1/T831AHNgCZi7WSAGLD60FnhwGWJIcjaMkhharJYV/UNIoWIdVZw8n4r/+gOaAq+KnruS613qX6I4Mv0pDxzpOr8yRtl2T0a5nk+Ke9FIuRXqt5g1PjNlRaAwNA6BH7DFGPPULBUwK9jEXG7pur3q/fnHbn02p9OQdVsgT2P7RjZf9gljEitRFj7Bzm8fQPGChPuDmrQ2YFc7U8tyHAaBxKlibbGTYq0VWch9CYobt3I8FZATkg9As/9OSgcDoC1+2/JtSMTwf7Xu0HWulNcAYWrssOX/hERrkrbGCdUjiOJFWtV9StTndVRFwqWZO4YJkhcUbmU4eo7s5OPv6Vyw0343UYv7hl36jdjTgEIwjDLCen/lcAK62w3oQvPb22+vEIJLAgzoEsvkSRJRmSwQtFXO7oUFAlfVYcIatMIAA3F64kV85mtKf+/R8Fa+sC2veUMbt/TIlsHWFPbpPivLN7XbFtaKABpFtc3ZW1fufI243yjzoKJNgyCiVbHzgNXR8gbCA3S3dAgHUfkOZxaHFR8ZY7rPFPOtBeADTsIBE+SlGAhGZlqVrYFQJy6BX8hH4XyTd0DzM3jK22ZiVYF/1fXYt8o/Dx27+lTCv0AVwQFDwLxp7ln91hyo0c8UiKY2SRQ5nG2ltzBQ89mc0T++NX33zgMsYPNz1lN0rpcp++cAgGNeTqzugjd9F1ONcxSslMVtQDuOMBHXEDHBbj14GdHJV8Nd+L26W2G0RI/i7AiCfSC2B6s6KDZUIk+ChYiXth+ioF74LeBG0/mipkQ7AVnBHxut5Qbj2YCoV6bVobxKIX4Jv1bMXBDh3xrOLm3If1ZjmKz5jQMpc4imGVTT5XaF86LQ4wIcRbbEK/za4Aasy/8N+/jrMkNcI2FSwgYOpP9wCsPr6dCainDtfWr/gdmt7xofCuGcAhwjHvv5Xbni59dCSVp0Q4JZw\"}]},\"native_finish_reason\":\"completed\"}],\"created\":1769348196,\"model\":\"x-ai/grok-4\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":6556,\"prompt_tokens\":1715,\"total_tokens\":8271,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":6518,\"rejected_prediction_tokens\":null,\"image_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":1198,\"video_tokens\":0},\"cost\":0.1007895,\"is_byok\":false,\"cost_details\":{\"upstream_inference_cost\":null,\"upstream_inference_prompt_cost\":0.0024495,\"upstream_inference_completions_cost\":0.09834}},\"provider\":\"xAI\"}"}, "scoring": {"f1_macro": 0.11, "f1_micro": 0.09, "cost_summary": {"total_input_tokens": 54624, "total_output_tokens": 122641, "total_tokens": 177265, "input_cost_usd": 0.16387200000000002, "output_cost_usd": 1.8396150000000002, "total_cost_usd": 2.0034870000000002}}, "normalized_score": 11.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b92"}, "test_id": "T0266", "benchmark": "business_letters", "date": "2026-01-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "x-ai/grok-4", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-11-08\"],\"letter_title\":null,\"sender_persons\":[\"H. W. Murray\"],\"receiver_persons\":[\"Christ\"]}}", "model": "x-ai/grok-4", "provider": "openrouter", "finish_reason": "stop", "usage": {"input_tokens": 1459, "output_tokens": 2662, "total_tokens": 4121, "cached_tokens": 1198, "input_cost_usd": 0.004377, "output_cost_usd": 0.03993, "estimated_cost_usd": 0.044307}, "duration": 50.8333523273468, "timestamp": "2026-01-25T12:45:44.105686", "parsed": {"metadata": {"send_date": ["1926-11-08"], "letter_title": null, "sender_persons": ["H. W. Murray"], "receiver_persons": ["Christ"], "document_number": "letter04"}}, "conversation_id": "f829085c-2c2b-4eba-84dc-9cbad8347bbe", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 1, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"gen-1769341493-V3NUNg8KjHT7mVzOYm5y\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\" {\\\"metadata\\\":{\\\"send_date\\\":[\\\"1926-11-08\\\"],\\\"letter_title\\\":null,\\\"sender_persons\\\":[\\\"H. W. Murray\\\"],\\\"receiver_persons\\\":[\\\"Christ\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1926-11-08\"],\"letter_title\":null,\"sender_persons\":[\"H. W. Murray\"],\"receiver_persons\":[\"Christ\"]}},\"reasoning\":null,\"reasoning_details\":[{\"id\":\"rs_30061b23-3edb-1631-42dc-53825bcd6777\",\"format\":\"xai-responses-v1\",\"index\":0,\"type\":\"reasoning.encrypted\",\"data\":\"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\"}]},\"native_finish_reason\":\"completed\"}],\"created\":1769341493,\"model\":\"x-ai/grok-4\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":2662,\"prompt_tokens\":1459,\"total_tokens\":4121,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":2627,\"rejected_prediction_tokens\":null,\"image_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":1198,\"video_tokens\":0},\"cost\":0.0416115,\"is_byok\":false,\"cost_details\":{\"upstream_inference_cost\":null,\"upstream_inference_prompt_cost\":0.0016815,\"upstream_inference_completions_cost\":0.03993}},\"provider\":\"xAI\"}"}, "scoring": {"f1_macro": 0.08, "f1_micro": 0.07, "cost_summary": {"total_input_tokens": 93659, "total_output_tokens": 200803, "total_tokens": 294462, "input_cost_usd": 0.2809770000000001, "output_cost_usd": 3.012045, "total_cost_usd": 3.2930219999999997}}, "normalized_score": 8.0}, {"_id": {"$oid": "69d4eb12b877594bc5718bb7"}, "test_id": "T0404", "benchmark": "business_letters", "date": "2026-01-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5.1-2025-11-13", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1935-08-17\"],\"letter_title\":null,\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Fritz Ritter\"]}}", "model": "gpt-5.1-2025-11-13", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 1398, "output_tokens": 54, "total_tokens": 1452, "input_cost_usd": 0.0017475, "output_cost_usd": 0.00054, "estimated_cost_usd": 0.0022875}, "duration": 3.2361507415771484, "timestamp": "2026-01-25T23:00:48.883572", "parsed": {"metadata": {"send_date": ["1935-08-17"], "letter_title": null, "sender_persons": ["Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["Fritz Ritter"], "document_number": "letter65"}}, "conversation_id": "faeeb5d5-6f2a-400b-91ee-1bdcdfe8d28f", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D22RzlHtQWYDSnfZ5zutCYJq9ifo0\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1935-08-17\\\"],\\\"letter_title\\\":null,\\\"sender_persons\\\":[\\\"Basler Personenschiffahrtsgesellschaft\\\"],\\\"receiver_persons\\\":[\\\"Fritz Ritter\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1935-08-17\"],\"letter_title\":null,\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Fritz Ritter\"]}}}}],\"created\":1769378447,\"model\":\"gpt-5.1-2025-11-13\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":54,\"prompt_tokens\":1398,\"total_tokens\":1452,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.54, "f1_micro": 0.57, "cost_summary": {"total_input_tokens": 116996, "total_output_tokens": 3471, "total_tokens": 120467, "input_cost_usd": 0.14624500000000007, "output_cost_usd": 0.03471, "total_cost_usd": 0.180955}}, "normalized_score": 54.0}, {"_id": {"$oid": "69d4eb12b877594bc5718bc1"}, "test_id": "T0267", "benchmark": "business_letters", "date": "2026-01-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "x-ai/grok-4", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1938-03-24\"],\"letter_title\":null,\"sender_persons\":[\"Hugo B\u00fcrkner\"],\"receiver_persons\":null}}", "model": "x-ai/grok-4", "provider": "openrouter", "finish_reason": "stop", "usage": {"input_tokens": 1459, "output_tokens": 2190, "total_tokens": 3649, "cached_tokens": 1198, "input_cost_usd": 0.004377, "output_cost_usd": 0.032850000000000004, "estimated_cost_usd": 0.037227}, "duration": 39.72493386268616, "timestamp": "2026-01-25T13:58:34.573426", "parsed": {"metadata": {"send_date": ["1938-03-24"], "letter_title": null, "sender_persons": ["Hugo B\u00fcrkner"], "receiver_persons": null, "document_number": "letter21"}}, "conversation_id": "ff7b68e0-ad8e-4cd9-98ed-c9e78fc2d5f8", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"gen-1769345875-0PObqpaT0YqoIExYxh1n\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\" {\\\"metadata\\\":{\\\"send_date\\\":[\\\"1938-03-24\\\"],\\\"letter_title\\\":null,\\\"sender_persons\\\":[\\\"Hugo B\u00fcrkner\\\"],\\\"receiver_persons\\\":null}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1938-03-24\"],\"letter_title\":null,\"sender_persons\":[\"Hugo 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\"}]},\"native_finish_reason\":\"completed\"}],\"created\":1769345875,\"model\":\"x-ai/grok-4\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":2190,\"prompt_tokens\":1459,\"total_tokens\":3649,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":2157,\"rejected_prediction_tokens\":null,\"image_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":1198,\"video_tokens\":0},\"cost\":0.0345315,\"is_byok\":false,\"cost_details\":{\"upstream_inference_cost\":null,\"upstream_inference_prompt_cost\":0.0016815,\"upstream_inference_completions_cost\":0.03285}},\"provider\":\"xAI\"}"}, "scoring": {"f1_macro": 0.04, "f1_micro": 0.02, "cost_summary": {"total_input_tokens": 39035, "total_output_tokens": 87018, "total_tokens": 126053, "input_cost_usd": 0.11710500000000004, "output_cost_usd": 1.30527, "total_cost_usd": 1.4223750000000002}}, "normalized_score": 4.0}, {"_id": {"$oid": "69d4eb12b877594bc5718bb4"}, "test_id": "T0566", "benchmark": "business_letters", "date": "2026-01-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "magistral-small-2509", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":null,\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":null}}", "model": "magistral-small-2509", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 32, "total_tokens": 617, "input_cost_usd": 0.0002925, "output_cost_usd": 1.6e-05, "estimated_cost_usd": 0.0003085}, "duration": 0.731511116027832, "timestamp": "2026-01-25T01:09:31.334077", "parsed": {"metadata": {"send_date": null, "letter_title": null, "sender_persons": null, "receiver_persons": null, "document_number": "letter01"}}, "conversation_id": "e45f1348-09fa-4319-ac93-bdfe83fad7d2", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"64c3528bfdf64a3dbc7300df938a03eb\",\"object\":\"chat.completion\",\"model\":\"magistral-small-2509\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":32,\"total_tokens\":617,\"num_cached_tokens\":128},\"created\":1769299771,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\\"metadata\\\": {\\\"send_date\\\": null, \\\"letter_title\\\": null, \\\"sender_persons\\\": null, \\\"receiver_persons\\\": null}}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": null, "normalized_score": null}, {"_id": {"$oid": "69d4eb12b877594bc5718be3"}, "test_id": "T0262", "benchmark": "business_letters", "date": "2026-01-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "qwen/qwen3-vl-8b-instruct", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-04-02\"],\"letter_title\":[\"Schiffahrt Basel-Rheinfelden\"],\"sender_persons\":[\"Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Kur- und Verkehrsverein, Rheinfelden\"]}}", "model": "qwen/qwen3-vl-8b-instruct", "provider": "openrouter", "finish_reason": "stop", "usage": {"input_tokens": 11854, "output_tokens": 87, "total_tokens": 11941, "input_cost_usd": 0.00094832, "output_cost_usd": 4.35e-05, "estimated_cost_usd": 0.00099182}, "duration": 6.132653474807739, "timestamp": "2026-01-25T04:38:26.287037", "parsed": {"metadata": {"send_date": ["1928-04-02"], "letter_title": ["Schiffahrt Basel-Rheinfelden"], "sender_persons": ["Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Kur- und Verkehrsverein, Rheinfelden"], "document_number": "letter22"}}, "conversation_id": "7cd2326e-a121-4ecc-ab7a-cb70e822c3af", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"gen-1769312300-o64KtU2HEi2KSC5dXxnq\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1928-04-02\\\"],\\n \\\"letter_title\\\": [\\\"Schiffahrt Basel-Rheinfelden\\\"],\\n \\\"sender_persons\\\": [\\\"Rheinschiffahrt-Aktiengesellschaft\\\"],\\n \\\"receiver_persons\\\": [\\\"Kur- und Verkehrsverein, Rheinfelden\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-04-02\"],\"letter_title\":[\"Schiffahrt Basel-Rheinfelden\"],\"sender_persons\":[\"Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Kur- und Verkehrsverein, Rheinfelden\"]}},\"reasoning\":null},\"native_finish_reason\":\"stop\"}],\"created\":1769312300,\"model\":\"qwen/qwen3-vl-8b-instruct\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":87,\"prompt_tokens\":11854,\"total_tokens\":11941,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":null,\"image_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0,\"video_tokens\":0},\"cost\":0.00219288,\"is_byok\":false,\"cost_details\":{\"upstream_inference_cost\":null,\"upstream_inference_prompt_cost\":0.00213372,\"upstream_inference_completions_cost\":0.00005916}},\"provider\":\"Together\"}"}, "scoring": {"f1_macro": 0.53, "f1_micro": 0.48, "cost_summary": {"total_input_tokens": 160438, "total_output_tokens": 2273, "total_tokens": 162711, "input_cost_usd": 0.01283504, "output_cost_usd": 0.0011365, "total_cost_usd": 0.013971540000000001}}, "normalized_score": 53.0}, {"_id": {"$oid": "69d4eb12b877594bc5718baa"}, "test_id": "T0405", "benchmark": "business_letters", "date": "2026-01-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5.1-2025-11-13", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-04-25\"],\"letter_title\":null,\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.G.\"]}}", "model": "gpt-5.1-2025-11-13", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 1398, "output_tokens": 62, "total_tokens": 1460, "input_cost_usd": 0.0017475, "output_cost_usd": 0.00062, "estimated_cost_usd": 0.0023675}, "duration": 3.5814759731292725, "timestamp": "2026-01-25T23:01:51.419688", "parsed": {"metadata": {"send_date": ["1928-04-25"], "letter_title": null, "sender_persons": ["Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["Basler Rheinschiffahrt A.G."], "document_number": "letter28"}}, "conversation_id": "1f5e67f2-d314-402b-b3f4-3529d8184675", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D22Szw8gZ2tMHYQmBH0jIx7Z3RMWK\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1928-04-25\\\"],\\\"letter_title\\\":null,\\\"sender_persons\\\":[\\\"Basler Personenschiffahrtsgesellschaft\\\"],\\\"receiver_persons\\\":[\\\"Basler Rheinschiffahrt A.G.\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-04-25\"],\"letter_title\":null,\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.G.\"]}}}}],\"created\":1769378509,\"model\":\"gpt-5.1-2025-11-13\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":62,\"prompt_tokens\":1398,\"total_tokens\":1460,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.47, "f1_micro": 0.57, "cost_summary": {"total_input_tokens": 44050, "total_output_tokens": 1500, "total_tokens": 45550, "input_cost_usd": 0.05506249999999998, "output_cost_usd": 0.015000000000000003, "total_cost_usd": 0.07006249999999999}}, "normalized_score": 47.0}, {"_id": {"$oid": "69d4eb12b877594bc5718bab"}, "test_id": "T0546", "benchmark": "business_letters", "date": "2026-01-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "ministral-14b-2512", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":null,\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":null}}", "model": "ministral-14b-2512", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 42, "total_tokens": 627, "input_cost_usd": 0.00011700000000000001, "output_cost_usd": 8.4e-06, "estimated_cost_usd": 0.0001254}, "duration": 0.5517168045043945, "timestamp": "2026-01-25T00:17:42.659955", "parsed": {"metadata": {"letter_title": null, "sender_persons": null, "send_date": null, "receiver_persons": null, "document_number": "letter29"}}, "conversation_id": "7df91258-8f88-44dd-b0c7-2f11a2780dc2", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"3991f00fc92d4300a2ccbb99cee05478\",\"object\":\"chat.completion\",\"model\":\"ministral-14b-2512\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":42,\"total_tokens\":627,\"num_cached_tokens\":576},\"created\":1769296662,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"sender_persons\\\": null,\\n \\\"send_date\\\": null,\\n \\\"receiver_persons\\\": null\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 18720, "total_output_tokens": 1980, "total_tokens": 20700, "input_cost_usd": 0.003743999999999998, "output_cost_usd": 0.0003959999999999997, "total_cost_usd": 0.004139999999999999}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718bcc"}, "test_id": "T0261", "benchmark": "business_letters", "date": "2026-01-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "qwen/qwen3-vl-8b-instruct", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-09-23\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft\"]}}", "model": "qwen/qwen3-vl-8b-instruct", "provider": "openrouter", "finish_reason": "stop", "usage": {"input_tokens": 1847, "output_tokens": 56, "total_tokens": 1903, "input_cost_usd": 0.00014776, "output_cost_usd": 2.8e-05, "estimated_cost_usd": 0.00017576}, "duration": 1.527381181716919, "timestamp": "2026-01-25T04:36:34.181822", "parsed": {"metadata": {"send_date": ["1932-09-23"], "letter_title": null, "sender_persons": null, "receiver_persons": ["Basler Rheinschiffahrt Aktiengesellschaft"], "document_number": "letter51"}}, "conversation_id": "d4b9db76-5981-4987-bd30-05f73655cf23", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"gen-1769312192-BFMibkJQsaw03QwvKitT\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"receiver_persons\\\": [\\\"Basler Rheinschiffahrt Aktiengesellschaft\\\"],\\n \\\"send_date\\\": [\\\"1932-09-23\\\"],\\n \\\"sender_persons\\\": null\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1932-09-23\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft\"]}},\"reasoning\":null},\"native_finish_reason\":\"stop\"}],\"created\":1769312192,\"model\":\"qwen/qwen3-vl-8b-instruct\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":56,\"prompt_tokens\":1847,\"total_tokens\":1903,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":null,\"image_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0,\"video_tokens\":0},\"cost\":0.00037166,\"is_byok\":false,\"cost_details\":{\"upstream_inference_cost\":null,\"upstream_inference_prompt_cost\":0.00033246,\"upstream_inference_completions_cost\":0.0000392}},\"provider\":\"Alibaba\"}"}, "scoring": {"f1_macro": 0.49, "f1_micro": 0.58, "cost_summary": {"total_input_tokens": 94796, "total_output_tokens": 1764, "total_tokens": 96560, "input_cost_usd": 0.00758368, "output_cost_usd": 0.000882, "total_cost_usd": 0.00846568}}, "normalized_score": 49.0}, {"_id": {"$oid": "69d4eb12b877594bc5718bd3"}, "test_id": "T0260", "benchmark": "business_letters", "date": "2026-01-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "qwen/qwen3-vl-8b-instruct", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-02-27\"],\"letter_title\":null,\"sender_persons\":[\"Basler Personenschiffahrts-Gesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.-G.\"]}}", "model": "qwen/qwen3-vl-8b-instruct", "provider": "openrouter", "finish_reason": "stop", "usage": {"input_tokens": 3112, "output_tokens": 72, "total_tokens": 3184, "input_cost_usd": 0.00024896, "output_cost_usd": 3.6e-05, "estimated_cost_usd": 0.00028496}, "duration": 4.852722644805908, "timestamp": "2026-01-25T04:30:22.321650", "parsed": {"metadata": {"send_date": ["1928-02-27"], "letter_title": null, "sender_persons": ["Basler Personenschiffahrts-Gesellschaft"], "receiver_persons": ["Basler Rheinschiffahrt A.-G."], "document_number": "letter16"}}, "conversation_id": "931ff7f2-89a1-468b-9358-34edab14de56", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"gen-1769311817-3vK7m3YbS6VZkgo2dSzd\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"receiver_persons\\\": [\\\"Basler Rheinschiffahrt A.-G.\\\"],\\n \\\"send_date\\\": [\\\"1928-02-27\\\"],\\n \\\"sender_persons\\\": [\\\"Basler Personenschiffahrts-Gesellschaft\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-02-27\"],\"letter_title\":null,\"sender_persons\":[\"Basler Personenschiffahrts-Gesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.-G.\"]}},\"reasoning\":null},\"native_finish_reason\":\"stop\"}],\"created\":1769311817,\"model\":\"qwen/qwen3-vl-8b-instruct\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":\"\",\"usage\":{\"completion_tokens\":72,\"prompt_tokens\":3112,\"total_tokens\":3184,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":null,\"image_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0,\"video_tokens\":0},\"cost\":0.00028496,\"is_byok\":false,\"cost_details\":{\"upstream_inference_cost\":null,\"upstream_inference_prompt_cost\":0.00024896,\"upstream_inference_completions_cost\":0.000036}},\"provider\":\"Novita\"}"}, "scoring": {"f1_macro": 0.5, "f1_micro": 0.51, "cost_summary": {"total_input_tokens": 265843, "total_output_tokens": 4201, "total_tokens": 270044, "input_cost_usd": 0.02126744, "output_cost_usd": 0.0021005, "total_cost_usd": 0.023367940000000004}}, "normalized_score": 50.0}, {"_id": {"$oid": "69d4eb12b877594bc5718bd9"}, "test_id": "T0502", "benchmark": "business_letters", "date": "2026-01-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-3-flash-preview", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-05-03\"],\"letter_title\":null,\"sender_persons\":[\"M. Ritter\",\"Gundling\"],\"receiver_persons\":[\"Max Vischer\"]}}", "model": "gemini-3-flash-preview", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 1428, "output_tokens": 69, "total_tokens": 64410, "input_cost_usd": 0.000714, "output_cost_usd": 0.000207, "estimated_cost_usd": 0.0009209999999999999}, "duration": 315.55846190452576, "timestamp": "2026-01-25T01:44:48.415116", "parsed": {"metadata": {"send_date": ["1928-05-03"], "letter_title": null, "sender_persons": ["M. Ritter", "Gundling"], "receiver_persons": ["Max Vischer"], "document_number": "letter31"}}, "conversation_id": "acd1591c-ceb2-4c6c-a491-e279a99489a1", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 2, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Sun, 25 Jan 2026 00:44:48 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=315371\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; 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\",\"function_call\":null,\"code_execution_result\":null,\"executable_code\":n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\\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1928-05-03\\\"],\\n \\\"letter_title\\\": null,\\n \\\"sender_persons\\\": [\\\"M. Ritter\\\", \\\"Gundling\\\"],\\n \\\"receiver_persons\\\": [\\\"Max Vischer\\\"]\\n }\\n}\"}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"url_context_metadata\":null,\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null}],\"create_time\":null,\"model_version\":\"gemini-3-flash-preview\",\"prompt_feedback\":null,\"response_id\":\"gGd1aaf6FMGdkdUPoMaz0Ao\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":69,\"candidates_tokens_details\":null,\"prompt_token_count\":1428,\"prompt_tokens_details\":[{\"modality\":\"IMAGE\",\"token_count\":1092},{\"modality\":\"TEXT\",\"token_count\":336}],\"thoughts_token_count\":62913,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":64410,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1928-05-03\"],\"letter_title\":null,\"sender_persons\":[\"M. Ritter\",\"Gundling\"],\"receiver_persons\":[\"Max Vischer\"]}}}"}, "scoring": {"f1_macro": 0.64, "f1_micro": 0.59, "cost_summary": {"total_input_tokens": 79548, "total_output_tokens": 1860, "total_tokens": 81408, "input_cost_usd": 0.03977399999999999, "output_cost_usd": 0.005580000000000002, "total_cost_usd": 0.04535400000000002}}, "normalized_score": 64.0}, {"_id": {"$oid": "69d4eb12b877594bc5718be0"}, "test_id": "T0567", "benchmark": "business_letters", "date": "2026-01-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "magistral-small-2509", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"null\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"null\"]}}", "model": "magistral-small-2509", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 37, "total_tokens": 622, "input_cost_usd": 0.0002925, "output_cost_usd": 1.85e-05, "estimated_cost_usd": 0.000311}, "duration": 0.45551085472106934, "timestamp": "2026-01-25T01:09:36.189292", "parsed": {"metadata": {"send_date": ["null"], "letter_title": ["null"], "sender_persons": ["null"], "receiver_persons": ["null"], "document_number": "letter06"}}, "conversation_id": "4367b5ba-fe40-4d5d-8821-92839bce301d", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"ddef3feed5b6427e889f63c68ae1d276\",\"object\":\"chat.completion\",\"model\":\"magistral-small-2509\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":37,\"total_tokens\":622,\"num_cached_tokens\":128},\"created\":1769299775,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\\"metadata\\\": {\\\"send_date\\\": [\\\"null\\\"], \\\"letter_title\\\": [\\\"null\\\"], \\\"sender_persons\\\": [\\\"null\\\"], \\\"receiver_persons\\\": [\\\"null\\\"]}}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": null, "normalized_score": null}, {"_id": {"$oid": "69d4eb12b877594bc5718bf2"}, "test_id": "T0568", "benchmark": "business_letters", "date": "2026-01-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "magistral-small-2509", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":null,\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":null}}", "model": "magistral-small-2509", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 35, "total_tokens": 620, "input_cost_usd": 0.0002925, "output_cost_usd": 1.75e-05, "estimated_cost_usd": 0.00031}, "duration": 0.7685317993164062, "timestamp": "2026-01-25T01:09:38.997180", "parsed": {"metadata": {"send_date": null, "letter_title": null, "sender_persons": null, "receiver_persons": null, "document_number": "letter01"}}, "conversation_id": "d3218f1f-720e-4a5b-b2ec-9b447d7ce2d6", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"2e35ffeed9804600a18a55d62dd457f3\",\"object\":\"chat.completion\",\"model\":\"magistral-small-2509\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":35,\"total_tokens\":620,\"num_cached_tokens\":704},\"created\":1769299778,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{ \\\"metadata\\\": { \\\"send_date\\\": null, \\\"letter_title\\\": null, \\\"sender_persons\\\": null, \\\"receiver_persons\\\": null } }\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": null, "normalized_score": null}, {"_id": {"$oid": "69d4eb12b877594bc5718bfd"}, "test_id": "T0406", "benchmark": "business_letters", "date": "2026-01-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5.1-2025-11-13", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-04-26\"],\"letter_title\":null,\"sender_persons\":[\"Basler Rheinschifffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Max Oettinger\"]}}", "model": "gpt-5.1-2025-11-13", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 1398, "output_tokens": 59, "total_tokens": 1457, "cached_tokens": 1280, "input_cost_usd": 0.0017475, "output_cost_usd": 0.00059, "estimated_cost_usd": 0.0023375}, "duration": 2.7439095973968506, "timestamp": "2026-01-25T23:03:54.789776", "parsed": {"metadata": {"send_date": ["1928-04-26"], "letter_title": null, "sender_persons": ["Basler Rheinschifffahrt-Aktiengesellschaft"], "receiver_persons": ["Max Oettinger"], "document_number": "letter29"}}, "conversation_id": "b04c6f7d-d79a-4563-8eab-c03a6602c909", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D22UzMoVAOJrel5CFmhgOSS56wGD7\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1928-04-26\\\"],\\\"letter_title\\\":null,\\\"sender_persons\\\":[\\\"Basler Rheinschifffahrt-Aktiengesellschaft\\\"],\\\"receiver_persons\\\":[\\\"Max Oettinger\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-04-26\"],\"letter_title\":null,\"sender_persons\":[\"Basler Rheinschifffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Max Oettinger\"]}}}}],\"created\":1769378633,\"model\":\"gpt-5.1-2025-11-13\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":59,\"prompt_tokens\":1398,\"total_tokens\":1457,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":1280}}}"}, "scoring": {"f1_macro": 0.6, "f1_micro": 0.55, "cost_summary": {"total_input_tokens": 72946, "total_output_tokens": 2004, "total_tokens": 74950, "input_cost_usd": 0.09118249999999997, "output_cost_usd": 0.020039999999999995, "total_cost_usd": 0.11122249999999999}}, "normalized_score": 60.0}, {"_id": {"$oid": "69d4eb12b877594bc5718bfe"}, "test_id": "T0501", "benchmark": "business_letters", "date": "2026-01-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-3-flash-preview", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-05-03\"],\"letter_title\":null,\"sender_persons\":[\"Ritter\",\"Groschupf\"],\"receiver_persons\":[\"W. Stauffacher\"]}}", "model": "gemini-3-flash-preview", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 1428, "output_tokens": 48, "total_tokens": 2604, "input_cost_usd": 0.000714, "output_cost_usd": 0.000144, "estimated_cost_usd": 0.000858}, "duration": 8.81415319442749, "timestamp": "2026-01-25T01:23:02.748632", "parsed": {"metadata": {"send_date": ["1928-05-03"], "letter_title": null, "sender_persons": ["Ritter", "Groschupf"], "receiver_persons": ["W. Stauffacher"], "document_number": "letter32"}}, "conversation_id": "02470d6d-ddd0-4928-9424-5a6a61043bb6", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 2, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Sun, 25 Jan 2026 00:23:02 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=8670\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"video_metadata\":null,\"thought\":null,\"inline_data\":null,\"file_data\":null,\"thought_signature\":\"ErIbCq8bAXLI2nwLF-CJk2tRd-ZapvqDEuhIvxMvxCKEHLlpSeXVKHsm3SGTaabNgFCybLyIaEixKhhgc5WNAd0vDMWh8PyW_C1eVUVDIpJxTEmC_uDP5Xe-zs0hp0l9o2rFeRoakaGvquoHGOzm7gfjIrfD8ooMyLmYXxKjPZSIqncMhAw9aIhzAkaOLCNwuhFXTaaZYHTiAaOrGbbBuOdJz0L0crEFD8NWQi2Zz2_T7VIM6VUamtQDiJPDJVFjW5-UdocTcgUfyv5TZvjtbSjwVfyms7vENfnfmiqycfS-_cUkrpD_YemJ2CdGLA6cdiF8tROWubnVHRDHABxZs_7WykFPDbkM-Ablg1kLOftY2qyR0FWw1G9AUpxukl6wClAitI6WymmXQp1fUoQGIK-RqNhLYzWHKUj8HlQcNMMpQeIziWoiAIl0brDNRoOd_r-A1j0dzn_eVptHscbuU8g83q81st0RKpkyxTVtDW9gOGdh1W09zwPrSeckGnmlAydYEMMNc-fBfg6ldUq7TwBAzfhKdA4pLEFyaMeIJFxHq6S-AkMa328OqijeLDGkIM-Oxw6aRu_D5uu8uwqwxZ7HnSRdt8nXVtab_FcvfKiUBx62_aRGpZRvqOKrXbgb-MJfAA1hHl9Jwinr4-VCeEv3FrlvA-KBOgLY0xEPG1JD__nFZQuA8eJE4KZGqnLeZ3cKtxvy-ROrLbPZjKvWJakNITYdboP3Jj615OA80YiKHd0w8HG4pf4U2WPqXuueKZECaYzX9vzEAK4qgkVf4uJ7G_KBqIVEfYhMcC14KJpySO0FA5fAjqVU0u51RCtPpjlqnira3MW6S5sBWTBVB3u-qQJVbLElqRwNHRPfAScz4ppulGinc0sHjgUqfrP5QtbENW9ufHRbvj9LEXLHBbodoNUtwREGW9h7R7CIt3ZkS66onwyKOV1pmSbq-VXd8VaOktCj23LQvxyfKqrGxDqvIm_PGQlzSQCiKtJbD-056Wil8C1jxXex6AXnvS0ZzB75K_NEtlmBMis7LnF0yZ5zHvAzgQU31t_iV2-AXriUf7gfMOtOrlyiIUIHJ9FMprqVq6ejuRNlxOCrUAja2fCAg15PXwx4Lp5yyX2xoXjufHN32sSdeBVcWHj9eirxBnan0T0cpXQQXoErYcMXGGg4dadTvzaFX0Bzh9Ub-XUP02w0vWN9XSq28EA9weJKipsJyH8Yi6mhj2Imfg5MTXLWtTS3BIO-LoKO3xj4VTOeeDoo9Nhsvu1RiCngFy8hX39aHL5RgCKsnXagfL2TwipKD6Cy15bhBZQcYfofsZS-WTWwtfrIX5FXEws3MmHk-UYtJ0vJr4474Icb55HmIYOTz7o7EZN-XxDabsFTSQFFXcJ3WGf3V3iYXWK8w1u0ItIokf9CahLsKh0OilGijHhaEwuRuhwOSMwdhSF15nFLbPx1aVgT2GPQZRn6T6OdaQzZEd9AeMaeBQcrJqv5mqv2i6_ArLiHZBBdrqGa2V1qpSRdfOPndjzoF3-zIFX8MDRVbuze-iw5MR-oMDpJA_jTDsngzIuvuhEWMa2izkdUoYnepsVxUH3CyzrHqbyWNE3rNqD5O4fWYQnYaIi3jqPBkUFZtvarsd-Fj0yZcJkxnyr0ukSrEXVZhvNINchJRLNdJs-bW7V_s9oc20aISU1lHr4LrL7zZJd1KUSGdVs8ujSKepP4wgr44vL3ujozd_E4AL_IL9mNtStu5XS2qhQaCjGAtiiPXg0unDGpBjOY4X5VgByyeY43V8dZkseF8ZGd13vJvkI1JTWf2ZIK4cNQzDjyEPa9i3RLHPWSFNP0IW8ln6c7pRflLrDsQdJFNtCTowh3Qrx79uNd9mKqJPXI-BcyhOZ2qyqeixmrzIth0BZMretImAvbmsatFdcLsmpEqmwQxJSYU9Kc1np7Dlr-D6iQyjev8xJIg8VKs2FRLe9k6IJI_gf6MVRkA3C20jGt_0zCbcmX5myIQRjRefwDR280rrb2nvwRVGkSJ8gZTQa8uq9vo51ZBEIamHOUbEp4oDAdJ2lvIueZfU2ljie-_7-HZsvoJA_sI-Gx4ZzySeUEoBzXaOYXsN5Q_fBZKhyf92loEHM-9pT3TysOUldTN86Dmc3OgJ2hJWYaI31XU5pbW6oJc9XWL6c9yL5l3-8fU6btgROrF5y01AeHLh7w5RfukoNqMmujDN3-xqt9YaNHua6q2WIMp1rKUIlJmYICZ8rBiKChoq4viT92cA2v9T_jiojIYxYNJZCO2t-RGP9k26yqCYoZAGW7BCqIH2KBd_yuhuZbzIVf0gzWqNaAb_oVfNK4mEe9eS-W512BqEvLbtzyoeTSjFSv_n41pb8KZug_M0GUtXnABACAc9mdnozGps3MTzvoErkm52cZ0QhuINqvRLKnOjDPhRs5wEtE0e0pvC9g2j84MvlX2hj3X6aiAOIE54uaIKNvk8vESFzEoTQgIJdvR-w-8b06c8IMGjwePUIiIChnQwqdD3hv4f7PK7Z49g1d6h0rtU76TMei8HcFhGkvBKiLuyVY0pMpuE_YPne7TQzwr1inbvfjVf0yJMP1pLmkucDUP_dULfXyEb9PjIvMLXf5ErXL-ZnVRkRqIqLoiWe47hNWL3UxXWOJ37fKt6crJgWg6MRwICi-NUMg_XZAyNAwv-AbVbSWnzug61Nult2hhgTtXtIV4PU6bXW9apLCRhi_u-DVRNk-Va_BbQk6AEQt0Hmk30-oTBqYqBbzMLrYRmUJ1ifDSAipMA1zW_sYQCfTF_jCF6YjDUJ__3tsGr1sBJJzncIjK2vO5HZx-Ze3W0bC125Yh-ReMdLkBQeHPiptSoxpcBU00B0AbVg2DikjRXr6sJbIHt9Zuhhxk72dE8Vw0L9SwlD2Zu9HovQRucugXc6rz2ZVPkicjBXYWGu_27gNj31nPJ5TkVRk7HYSbYiWKTkKqAonGgh1NBrUQiF5ZnCA4atkCjaAD5GF1xYkHRYa0Stg35UjUf33Fiy3JpjhEIbLQvStRV-0YGTzdPkPwmrk3mKAQ5ojhpn5ScbX-miMfTg9PuZv7DLKjH3Z4eM_4X1NTKWQB0tmTytjbetvKPJ5TppDEGdtl2pApPP4Q955J2MisjFZD_mNSOu8gZUzZSTR_zaIRS9_5rhMPPVqM2UCFjcC8fFf10YkuJJYY4Z4wQwvxYkKbG9qmU2a6DEJAkiVe32HLSSH3lU6pG7OmPVBKcWzU-3ffNXUPJtBpbMn9EMLF8G7IgGHNoRc4Kb7_PITSTZ9-4OH22NsrthuX5qn3jPaZg8XCbya4DKKaY2PBMyZEgdEviPsEp8jMSsbWZ5P1-uSG36LaXKq_tgZyKnE2tD7cESNdbzHYFIUwYfZI27XhlrAZQDkJywS05-XkM_yR0bFw2DpfaYfzP1q1T71AQy0xqE8htDg8pHHNFkiUbbePEgdBzvbSDOwr2SiDkgMeJKnARwdpcG0RNmv9zvPJWJE0-kyhsA5w3Tt1TU0fNoGAOPxhzBE9V7HVJ0TOdIPEoN1ihb6MkPYQeNNpnn0orSDuFGGdKBGwjq4TkmqAVpJp98L5ueOiSQUud05zxvYBisx0ewaCNf1EzMBnGGrB83tUelgzCcSdNrZrh7d3UYFf9lyfXHDCuju81_j6Rycujw69L84NpMxsmn4HHV3b_K5NgFq2ncXoI4XECF0gjiVpQfFJubYKewK_JN-HTP4rnHgPtfYyRRuXjkT3l3wFisDxNXwD3i_d6ccyC6UoZOHOePClSIkHrwTMArjErWeHFMVrs5vncEgXI03HSvePqZKxf8JTXUv9dvZaAanLNfC2GgkAPW9isjEADtqf3JApUtSPvsHPWUURjV8zwSqDWouScMnE_3oTOXOzD37xTtvb0isOMEDjQqaRwqLMbigopyqMZuVsifTTfpsKlXLRWdakCIewvnNjfddxqIgKB6L7C-8z6fZLCecFoahJd96WmA2i0RGIMwAsbFzduzHreAI7f4Fwb7YWBWpmbJdyGPHYM9Q0-9AdKqO9ATDHzgjGIOv36Rs5XZF67-IjmXVWtIDQ1PMBFDJQmST2ollIyujnEd-YHCwJl1pWmT5LfnzAewKBFpchBMBg11nacCZiyAZpHJvv_YrSUcaAQ6BBo5MK0iWuPSse5MMHj6F-Kfcp2PSha-3tjTfDhOAG7uslva5XHv_qSxFrEPLR_vPpqQP3Ec16sSS9tnRdGhJ1myjp3CmiraWk5f9sosnqZIU0zmjKyRPv-yBrAD7_nC8wVlpE0CcgAvWGwHfgIaxTrgLRgBdHNMbzmQWnoLorVRXnnmHl86MHCRqMNS4gnaVbaorUXVBmLT3HTkIn3cDPcIO1lkcnohAeWNo-ueVyOyeRrw6-jgSLWC63QjrkgIB5D29YxxTjzN6AXHP34oG_o8H6LFGv_FWKX0eOiwJ4EE18KV_pyQZKTFuUnfNKGYnr2y0S-KlyzW8luhjsSNHgAN3pBzi7uwR-7w1T8ZTsGgwmuvGBVIpzDZ7Qw9YhFMVKw3pjGZLs4RnFZRpZIKF5T_Ujca12BLTRjxZufFOIrmvx9UjbOdo0nd6GaGJg6baHn_ckvx6Q_UrxeKlc30hOygL2HQetY9eTypjLTNnFpkMC3_FCLUvMQeWWfmFoa26kfKAaeE=\",\"function_call\":null,\"code_execution_result\":null,\"executable_code\":null,\"function_response\":null,\"text\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1928-05-03\\\"],\\\"letter_title\\\":null,\\\"sender_persons\\\":[\\\"Ritter\\\",\\\"Groschupf\\\"],\\\"receiver_persons\\\":[\\\"W. Stauffacher\\\"]}}\"}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"url_context_metadata\":null,\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null}],\"create_time\":null,\"model_version\":\"gemini-3-flash-preview\",\"prompt_feedback\":null,\"response_id\":\"ZmJ1aeyHKrPk7M8Phpv-4AI\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":48,\"candidates_tokens_details\":null,\"prompt_token_count\":1428,\"prompt_tokens_details\":[{\"modality\":\"IMAGE\",\"token_count\":1092},{\"modality\":\"TEXT\",\"token_count\":336}],\"thoughts_token_count\":1128,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":2604,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1928-05-03\"],\"letter_title\":null,\"sender_persons\":[\"Ritter\",\"Groschupf\"],\"receiver_persons\":[\"W. Stauffacher\"]}}}"}, "scoring": {"f1_macro": 0.72, "f1_micro": 0.84, "cost_summary": {"total_input_tokens": 46620, "total_output_tokens": 1157, "total_tokens": 47777, "input_cost_usd": 0.023309999999999997, "output_cost_usd": 0.003470999999999999, "total_cost_usd": 0.026781000000000003}}, "normalized_score": 72.0}, {"_id": {"$oid": "69d4eb12b877594bc5718c00"}, "test_id": "T0544", "benchmark": "business_letters", "date": "2026-01-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "ministral-14b-2512", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":null,\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":null}}", "model": "ministral-14b-2512", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 42, "total_tokens": 627, "input_cost_usd": 0.00011700000000000001, "output_cost_usd": 8.4e-06, "estimated_cost_usd": 0.0001254}, "duration": 0.5315520763397217, "timestamp": "2026-01-25T00:16:53.792176", "parsed": {"metadata": {"letter_title": null, "sender_persons": null, "send_date": null, "receiver_persons": null, "document_number": "letter43"}}, "conversation_id": "c52be19e-0fc0-4f8f-b547-27a8426e8057", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"3bf20f94603844e49b774c6949b205f1\",\"object\":\"chat.completion\",\"model\":\"ministral-14b-2512\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":42,\"total_tokens\":627,\"num_cached_tokens\":576},\"created\":1769296613,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"sender_persons\\\": null,\\n \\\"send_date\\\": null,\\n \\\"receiver_persons\\\": null\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 33345, "total_output_tokens": 3030, "total_tokens": 36375, "input_cost_usd": 0.006668999999999996, "output_cost_usd": 0.0006059999999999996, "total_cost_usd": 0.007275000000000006}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718c01"}, "test_id": "T0545", "benchmark": "business_letters", "date": "2026-01-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "ministral-14b-2512", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":null,\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":null}}", "model": "ministral-14b-2512", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 42, "total_tokens": 627, "input_cost_usd": 0.00011700000000000001, "output_cost_usd": 8.4e-06, "estimated_cost_usd": 0.0001254}, "duration": 0.5397336483001709, "timestamp": "2026-01-25T00:17:16.946047", "parsed": {"metadata": {"letter_title": null, "sender_persons": null, "send_date": null, "receiver_persons": null, "document_number": "letter28"}}, "conversation_id": "ff8c7f90-e75f-4713-85ac-2a8aa2d8377b", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"be8d87525bf6474a86cb21a7d64e8a91\",\"object\":\"chat.completion\",\"model\":\"ministral-14b-2512\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":42,\"total_tokens\":627,\"num_cached_tokens\":576},\"created\":1769296636,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"sender_persons\\\": null,\\n \\\"send_date\\\": null,\\n \\\"receiver_persons\\\": null\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 14625, "total_output_tokens": 1050, "total_tokens": 15675, "input_cost_usd": 0.0029249999999999988, "output_cost_usd": 0.00020999999999999987, "total_cost_usd": 0.0031349999999999985}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718b0c"}, "test_id": "T0078", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4o-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-12-19\"],\"letter_title\":[\"Betr. Personenschifffahrt\"],\"sender_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft\"],\"receiver_persons\":[\"Dr. W. Vischer - von Planta\"]}}", "model": "gpt-4o-mini-2024-07-18", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 37324, "output_tokens": 71, "total_tokens": 37395, "cached_tokens": 1280, "input_cost_usd": 0.0055986000000000005, "output_cost_usd": 4.26e-05, "estimated_cost_usd": 0.005641200000000001}, "duration": 3.482172727584839, "timestamp": "2026-01-24T13:00:36.826370", "parsed": {"metadata": {"send_date": ["1932-12-19"], "letter_title": ["Betr. Personenschifffahrt"], "sender_persons": ["Basler Rheinschiffahrt Aktiengesellschaft"], "receiver_persons": ["Dr. W. Vischer - von Planta"], "document_number": "letter60"}}, "conversation_id": "e42696a4-8ecf-4470-8a99-0d1c1b817db7", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"chatcmpl-D1Wbaa0s4A0P9JsPG7yUOiGAsjcES\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1932-12-19\\\"],\\n \\\"letter_title\\\": [\\\"Betr. Personenschifffahrt\\\"],\\n \\\"sender_persons\\\": [\\\"Basler Rheinschiffahrt Aktiengesellschaft\\\"],\\n \\\"receiver_persons\\\": [\\\"Dr. W. Vischer - von Planta\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1932-12-19\"],\"letter_title\":[\"Betr. Personenschifffahrt\"],\"sender_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft\"],\"receiver_persons\":[\"Dr. W. Vischer - von Planta\"]}}}}],\"created\":1769256034,\"model\":\"gpt-4o-mini-2024-07-18\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":\"fp_8bbc38b4db\",\"usage\":{\"completion_tokens\":71,\"prompt_tokens\":37324,\"total_tokens\":37395,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":1280}}}"}, "scoring": {"f1_macro": 0.53, "f1_micro": 0.48, "cost_summary": {"total_input_tokens": 2336253, "total_output_tokens": 2244, "total_tokens": 2338497, "input_cost_usd": 0.3504379500000001, "output_cost_usd": 0.0013463999999999998, "total_cost_usd": 0.3517843499999999}}, "normalized_score": 53.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b1b"}, "test_id": "T0100", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-opus-4-20250514", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-03-24\"],\"letter_title\":null,\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"P. Christ - Wackermagel\",\"Fa. Paravicini, Christ & Co.\"]}}", "model": "claude-opus-4-20250514", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 2514, "output_tokens": 121, "total_tokens": 2635, "input_cost_usd": 0.03771, "output_cost_usd": 0.009075, "estimated_cost_usd": 0.046785}, "duration": 5.403224945068359, "timestamp": "2026-01-24T11:13:45.018749", "parsed": {"metadata": {"letter_title": null, "send_date": ["1926-03-24"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["P. Christ - Wackermagel", "Fa. Paravicini, Christ & Co."], "document_number": "letter03"}}, "conversation_id": "8cdc1f6f-16fe-4914-a3ea-3e2521c5fb5e", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 2, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"msg_01NxRYG1v4mhnmbWRnawtSCw\",\"content\":[{\"id\":\"toolu_01YUqRvYawMcJvbZ56DTez3N\",\"input\":{\"metadata\":{\"letter_title\":null,\"send_date\":[\"1926-03-24\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"P. Christ - Wackermagel\",\"Fa. Paravicini, Christ & Co.\"],\"document_number\":\"letter03\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\"}],\"model\":\"claude-opus-4-20250514\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"input_tokens\":2514,\"output_tokens\":121,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.44, "f1_micro": 0.45, "cost_summary": {"total_input_tokens": 207012, "total_output_tokens": 6294, "total_tokens": 213306, "input_cost_usd": 3.105180000000002, "output_cost_usd": 0.4720500000000001, "total_cost_usd": 3.57723}}, "normalized_score": 44.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b42"}, "test_id": "T0513", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-opus-4-5-20251101", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-03-01\"],\"letter_title\":[\"Betrifft Ihr Schreiben vom 27. Februar\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Basler Personenschiffahrtsgesellschaft\"]}}", "model": "claude-opus-4-5-20251101", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 4341, "output_tokens": 111, "total_tokens": 4452, "input_cost_usd": 0.021705000000000002, "output_cost_usd": 0.002775, "estimated_cost_usd": 0.024480000000000002}, "duration": 5.544484853744507, "timestamp": "2026-01-24T16:37:22.126549", "parsed": {"metadata": {"send_date": ["1928-03-01"], "letter_title": ["Betrifft Ihr Schreiben vom 27. Februar"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Basler Personenschiffahrtsgesellschaft"], "document_number": "letter17"}}, "conversation_id": "9d8febeb-7522-4c24-9b3d-ac62f1e3f23f", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"msg_01RzBmbMT2vBrvQe3yBJg4Ru\",\"content\":[{\"id\":\"toolu_01WpStg49vW7FhWw8wjXKuBN\",\"input\":{\"metadata\":{\"send_date\":[\"1928-03-01\"],\"letter_title\":[\"Betrifft Ihr Schreiben vom 27. Februar\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"document_number\":\"letter17\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\"}],\"model\":\"claude-opus-4-5-20251101\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"input_tokens\":4341,\"output_tokens\":111,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.62, "f1_micro": 0.58, "cost_summary": {"total_input_tokens": 137358, "total_output_tokens": 2917, "total_tokens": 140275, "input_cost_usd": 0.6867899999999998, "output_cost_usd": 0.072925, "total_cost_usd": 0.759715}}, "normalized_score": 62.0}, {"_id": {"$oid": "69d4eb12b877594bc5718adc"}, "test_id": "T0068", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4.1", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1935-08-15\"],\"letter_title\":[\"\"],\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrts A.-G.\"]}}", "model": "gpt-4.1-2025-04-14", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 1594, "output_tokens": 65, "total_tokens": 1659, "input_cost_usd": 0.003188, "output_cost_usd": 0.00052, "estimated_cost_usd": 0.003708}, "duration": 2.753039598464966, "timestamp": "2026-01-24T12:34:38.384022", "parsed": {"metadata": {"send_date": ["1935-08-15"], "letter_title": [""], "sender_persons": ["Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["Basler Rheinschiffahrts A.-G."], "document_number": "letter63"}}, "conversation_id": "0c5fad8d-3d96-4620-bd36-a02764bfaee7", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D1WCSko71TtaQRpgUWxj9rG2mRaev\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1935-08-15\\\"],\\n \\\"letter_title\\\": [\\\"\\\"],\\n \\\"sender_persons\\\": [\\\"Basler Personenschiffahrtsgesellschaft\\\"],\\n \\\"receiver_persons\\\": [\\\"Basler Rheinschiffahrts A.-G.\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1935-08-15\"],\"letter_title\":[\"\"],\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrts A.-G.\"]}}}}],\"created\":1769254476,\"model\":\"gpt-4.1-2025-04-14\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":\"fp_1a2c4a5ede\",\"usage\":{\"completion_tokens\":65,\"prompt_tokens\":1594,\"total_tokens\":1659,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.43, "f1_micro": 0.52, "cost_summary": {"total_input_tokens": 50900, "total_output_tokens": 1595, "total_tokens": 52495, "input_cost_usd": 0.10179999999999996, "output_cost_usd": 0.012759999999999999, "total_cost_usd": 0.11456000000000001}}, "normalized_score": 43.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b4e"}, "test_id": "T0069", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4.1", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-10-07\"],\"letter_title\":[\"\"],\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Vorstandsmitglieder der Basler Personenschiffahrtsgesellschaft\"]}}", "model": "gpt-4.1-2025-04-14", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 1594, "output_tokens": 67, "total_tokens": 1661, "input_cost_usd": 0.003188, "output_cost_usd": 0.000536, "estimated_cost_usd": 0.003724}, "duration": 2.900681257247925, "timestamp": "2026-01-24T12:37:07.156878", "parsed": {"metadata": {"send_date": ["1932-10-07"], "letter_title": [""], "sender_persons": ["Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["Vorstandsmitglieder der Basler Personenschiffahrtsgesellschaft"], "document_number": "letter53"}}, "conversation_id": "ce9c53b5-20e1-4dac-be85-a0afa013a276", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D1WEr1crIlNBRfgnszZ6mexLrEuwY\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1932-10-07\\\"],\\n \\\"letter_title\\\": [\\\"\\\"],\\n \\\"sender_persons\\\": [\\\"Basler Personenschiffahrtsgesellschaft\\\"],\\n \\\"receiver_persons\\\": [\\\"Vorstandsmitglieder der Basler Personenschiffahrtsgesellschaft\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1932-10-07\"],\"letter_title\":[\"\"],\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Vorstandsmitglieder der Basler Personenschiffahrtsgesellschaft\"]}}}}],\"created\":1769254625,\"model\":\"gpt-4.1-2025-04-14\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":\"fp_1a2c4a5ede\",\"usage\":{\"completion_tokens\":67,\"prompt_tokens\":1594,\"total_tokens\":1661,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.58, "f1_micro": 0.53, "cost_summary": {"total_input_tokens": 85263, "total_output_tokens": 2056, "total_tokens": 87319, "input_cost_usd": 0.17052599999999998, "output_cost_usd": 0.016448000000000004, "total_cost_usd": 0.18697399999999997}}, "normalized_score": 57.99999999999999}, {"_id": {"$oid": "69d4eb12b877594bc5718aef"}, "test_id": "T0206", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-flash-lite", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-06-22\"],\"letter_title\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"sender_persons\":[\"J. Grieder\",\"Dr. H. M\u00fcller\"],\"receiver_persons\":[\"Herrn P. Christ\"]}}", "model": "gemini-2.5-flash-lite", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 594, "output_tokens": 111, "total_tokens": 705, "input_cost_usd": 5.940000000000001e-05, "output_cost_usd": 4.44e-05, "estimated_cost_usd": 0.0001038}, "duration": 1.2218685150146484, "timestamp": "2026-01-24T13:35:21.161685", "parsed": {"metadata": {"send_date": ["1926-06-22"], "letter_title": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "sender_persons": ["J. Grieder", "Dr. H. M\u00fcller"], "receiver_persons": ["Herrn P. Christ"], "document_number": "letter07"}}, "conversation_id": "60a06100-3a33-46fe-be47-772006294fe4", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 2, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Sat, 24 Jan 2026 12:35:21 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=1072\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"video_metadata\":null,\"thought\":null,\"inline_data\":null,\"file_data\":null,\"thought_signature\":null,\"function_call\":null,\"code_execution_result\":null,\"executable_code\":null,\"function_response\":null,\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1926-06-22\\\"\\n ],\\n \\\"letter_title\\\": [\\n \\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"\\n ],\\n \\\"sender_persons\\\": [\\n \\\"J. Grieder\\\",\\n \\\"Dr. H. M\u00fcller\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Herrn P. Christ\\\"\\n ]\\n }\\n}\"}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"url_context_metadata\":null,\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null}],\"create_time\":null,\"model_version\":\"gemini-2.5-flash-lite\",\"prompt_feedback\":null,\"response_id\":\"ibx0abX9BLWLkdUPxNOiKQ\",\"usage_metadata\":{\"cache_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":264},{\"modality\":\"IMAGE\",\"token_count\":202}],\"cached_content_token_count\":466,\"candidates_token_count\":111,\"candidates_tokens_details\":null,\"prompt_token_count\":594,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":336},{\"modality\":\"IMAGE\",\"token_count\":258}],\"thoughts_token_count\":null,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":705,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1926-06-22\"],\"letter_title\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"sender_persons\":[\"J. Grieder\",\"Dr. H. M\u00fcller\"],\"receiver_persons\":[\"Herrn P. Christ\"]}}}"}, "scoring": {"f1_macro": 0.49, "f1_micro": 0.44, "cost_summary": {"total_input_tokens": 27006, "total_output_tokens": 3604, "total_tokens": 30610, "input_cost_usd": 0.0027006000000000005, "output_cost_usd": 0.0014416, "total_cost_usd": 0.0041422}}, "normalized_score": 49.0}, {"_id": {"$oid": "69d4eb12b877594bc5718aa9"}, "test_id": "T0212", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-flash-lite-preview-09-2025", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-07-13\"],\"letter_title\":[\"Betr. \\\"ALBATROS\\\".\"],\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Elektrizit\u00e4tswerk, Basel\"]}}", "model": "gemini-2.5-flash-lite-preview-09-2025", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 594, "output_tokens": 104, "total_tokens": 699, "input_cost_usd": 5.940000000000001e-05, "output_cost_usd": 4.16e-05, "estimated_cost_usd": 0.00010100000000000002}, "duration": 0.8919708728790283, "timestamp": "2026-01-24T13:50:57.974347", "parsed": {"metadata": {"send_date": ["1926-07-13"], "letter_title": ["Betr. \"ALBATROS\"."], "sender_persons": ["Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["Elektrizit\u00e4tswerk, Basel"], "document_number": "letter10"}}, "conversation_id": "d85f960f-06ed-4d6f-b984-c76fb018df0b", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Sat, 24 Jan 2026 12:50:57 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=746\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"video_metadata\":null,\"thought\":null,\"inline_data\":null,\"file_data\":null,\"thought_signature\":null,\"function_call\":null,\"code_execution_result\":null,\"executable_code\":null,\"function_response\":null,\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1926-07-13\\\"\\n ],\\n \\\"letter_title\\\": [\\n \\\"Betr. \\\\\\\"ALBATROS\\\\\\\".\\\"\\n ],\\n \\\"sender_persons\\\": [\\n \\\"Basler Personenschiffahrtsgesellschaft\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Elektrizit\u00e4tswerk, Basel\\\"\\n ]\\n }\\n}\"}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"url_context_metadata\":null,\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null}],\"create_time\":null,\"model_version\":\"gemini-2.5-flash-lite-preview-09-2025\",\"prompt_feedback\":null,\"response_id\":\"McB0adjiNpLs7M8P4O3d6Ao\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":104,\"candidates_tokens_details\":null,\"prompt_token_count\":594,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":336},{\"modality\":\"IMAGE\",\"token_count\":258}],\"thoughts_token_count\":1,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":699,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1926-07-13\"],\"letter_title\":[\"Betr. \\\"ALBATROS\\\".\"],\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Elektrizit\u00e4tswerk, Basel\"]}}}"}, "scoring": {"f1_macro": 0.46, "f1_micro": 0.46, "cost_summary": {"total_input_tokens": 44436, "total_output_tokens": 6330, "total_tokens": 50766, "input_cost_usd": 0.004443600000000001, "output_cost_usd": 0.002532000000000001, "total_cost_usd": 0.006975600000000002}}, "normalized_score": 46.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b75"}, "test_id": "T0119", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-opus-4-1-20250805", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1935-08-16\"],\"letter_title\":null,\"sender_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft\"],\"receiver_persons\":[\"Basler Personenschiffahrts-Gesellschaft\"]}}", "model": "claude-opus-4-1-20250805", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 2514, "output_tokens": 109, "total_tokens": 2623, "input_cost_usd": 0.03771, "output_cost_usd": 0.008175, "estimated_cost_usd": 0.045885}, "duration": 4.274930477142334, "timestamp": "2026-01-24T11:45:00.730650", "parsed": {"metadata": {"letter_title": null, "send_date": ["1935-08-16"], "sender_persons": ["Basler Rheinschiffahrt Aktiengesellschaft"], "receiver_persons": ["Basler Personenschiffahrts-Gesellschaft"], "document_number": "letter64"}}, "conversation_id": "71fbaa34-f96d-4ab9-acaf-d4f4bb3ffaed", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"msg_01EKtiQ69jLahTM69Z7pM8qP\",\"content\":[{\"id\":\"toolu_01Kf8rLHuYgbHqV7oZ6rawv5\",\"input\":{\"metadata\":{\"letter_title\":null,\"send_date\":[\"1935-08-16\"],\"sender_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft\"],\"receiver_persons\":[\"Basler Personenschiffahrts-Gesellschaft\"],\"document_number\":\"letter64\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\"}],\"model\":\"claude-opus-4-1-20250805\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"input_tokens\":2514,\"output_tokens\":109,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.48, "f1_micro": 0.44, "cost_summary": {"total_input_tokens": 128622, "total_output_tokens": 3514, "total_tokens": 132136, "input_cost_usd": 1.9293299999999993, "output_cost_usd": 0.26354999999999995, "total_cost_usd": 2.1928800000000006}}, "normalized_score": 48.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b63"}, "test_id": "T0227", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-sonnet-4-5-20250929", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1938-08-15\"],\"letter_title\":null,\"sender_persons\":[\"Basler Personenschifffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrts A.-G.\"]}}", "model": "claude-sonnet-4-5-20250929", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 2787, "output_tokens": 104, "total_tokens": 2891, "input_cost_usd": 0.008361, "output_cost_usd": 0.00156, "estimated_cost_usd": 0.009921000000000001}, "duration": 3.211905002593994, "timestamp": "2026-01-24T13:59:04.526795", "parsed": {"metadata": {"letter_title": null, "send_date": ["1938-08-15"], "sender_persons": ["Basler Personenschifffahrtsgesellschaft"], "receiver_persons": ["Basler Rheinschiffahrts A.-G."], "document_number": "letter63"}}, "conversation_id": "0a0a270a-9be7-4db5-8157-7c58e79aca6d", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"msg_01UkQqxwmc7Smsek6zWhAQbt\",\"content\":[{\"id\":\"toolu_01QNkERaDw5fnxgR59sr2KLT\",\"input\":{\"metadata\":{\"letter_title\":null,\"send_date\":[\"1938-08-15\"],\"sender_persons\":[\"Basler Personenschifffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrts A.-G.\"],\"document_number\":\"letter63\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\"}],\"model\":\"claude-sonnet-4-5-20250929\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"input_tokens\":2787,\"output_tokens\":104,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.45, "f1_micro": 0.5, "cost_summary": {"total_input_tokens": 85215, "total_output_tokens": 2447, "total_tokens": 87662, "input_cost_usd": 0.2556450000000001, "output_cost_usd": 0.036705, "total_cost_usd": 0.29234999999999994}}, "normalized_score": 45.0}, {"_id": {"$oid": "69d4eb12b877594bc5718ad4"}, "test_id": "T0010", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4o", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1935-08-17\"],\"letter_title\":null,\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Fritz Ritter\"]}}", "model": "gpt-4o-2024-08-06", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 1594, "output_tokens": 42, "total_tokens": 1636, "input_cost_usd": 0.003985, "output_cost_usd": 0.00041999999999999996, "estimated_cost_usd": 0.004405}, "duration": 3.5172345638275146, "timestamp": "2026-01-24T11:11:02.733573", "parsed": {"metadata": {"send_date": ["1935-08-17"], "letter_title": null, "sender_persons": ["Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["Fritz Ritter"], "document_number": "letter65"}}, "conversation_id": "076f78b7-f0e2-4ad9-8ed5-d84f0d557654", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D1UtYPht4qhaNfF73UkmX4Pfr9czF\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1935-08-17\\\"],\\\"letter_title\\\":null,\\\"sender_persons\\\":[\\\"Basler Personenschiffahrtsgesellschaft\\\"],\\\"receiver_persons\\\":[\\\"Fritz Ritter\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1935-08-17\"],\"letter_title\":null,\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Fritz Ritter\"]}}}}],\"created\":1769249460,\"model\":\"gpt-4o-2024-08-06\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":\"fp_deacdd5f6f\",\"usage\":{\"completion_tokens\":42,\"prompt_tokens\":1594,\"total_tokens\":1636,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.51, "f1_micro": 0.52, "cost_summary": {"total_input_tokens": 136163, "total_output_tokens": 2697, "total_tokens": 138860, "input_cost_usd": 0.3404075000000001, "output_cost_usd": 0.02697, "total_cost_usd": 0.3673774999999999}}, "normalized_score": 51.0}, {"_id": {"$oid": "69d4eb12b877594bc5718a8e"}, "test_id": "T0045", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.0-flash", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-04-02\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"RHEINSCHIFFAHRT-AKTIENGESELLSCHAFT\"],\"receiver_persons\":[\"Basler Personenschiffahrtsgesellschaft\",\"Kur- und Verkehrsverein Rheinfelden\"]}}", "model": "gemini-2.0-flash", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 1429, "output_tokens": 120, "total_tokens": 1549, "input_cost_usd": 0.0001429, "output_cost_usd": 4.8e-05, "estimated_cost_usd": 0.0001909}, "duration": 2.2251391410827637, "timestamp": "2026-01-24T11:10:11.840770", "parsed": {"metadata": {"send_date": ["1928-04-02"], "letter_title": ["null"], "sender_persons": ["RHEINSCHIFFAHRT-AKTIENGESELLSCHAFT"], "receiver_persons": ["Basler Personenschiffahrtsgesellschaft", "Kur- und Verkehrsverein Rheinfelden"], "document_number": "letter22"}}, "conversation_id": "3f0a351e-0578-4120-a045-04b96ed87180", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 2, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Sat, 24 Jan 2026 10:10:11 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=1585\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"video_metadata\":null,\"thought\":null,\"inline_data\":null,\"file_data\":null,\"thought_signature\":null,\"function_call\":null,\"code_execution_result\":null,\"executable_code\":null,\"function_response\":null,\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1928-04-02\\\"\\n ],\\n \\\"letter_title\\\": [\\n \\\"null\\\"\\n ],\\n \\\"sender_persons\\\": [\\n \\\"RHEINSCHIFFAHRT-AKTIENGESELLSCHAFT\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Basler Personenschiffahrtsgesellschaft\\\",\\n \\\"Kur- und Verkehrsverein Rheinfelden\\\"\\n ]\\n }\\n}\"}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"url_context_metadata\":null,\"avg_logprobs\":-0.005344551304976145,\"grounding_metadata\":null,\"index\":null,\"logprobs_result\":null,\"safety_ratings\":null}],\"create_time\":null,\"model_version\":\"gemini-2.0-flash\",\"prompt_feedback\":null,\"response_id\":\"gpp0aee0FJLs7M8P8-3d6Ao\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":120,\"candidates_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":120}],\"prompt_token_count\":1429,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":397},{\"modality\":\"IMAGE\",\"token_count\":1032}],\"thoughts_token_count\":null,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":1549,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1928-04-02\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"RHEINSCHIFFAHRT-AKTIENGESELLSCHAFT\"],\"receiver_persons\":[\"Basler Personenschiffahrtsgesellschaft\",\"Kur- und Verkehrsverein Rheinfelden\"]}}}"}, "scoring": {"f1_macro": 0.53, "f1_micro": 0.48, "cost_summary": {"total_input_tokens": 52178, "total_output_tokens": 2832, "total_tokens": 55010, "input_cost_usd": 0.005217799999999998, "output_cost_usd": 0.0011328000000000002, "total_cost_usd": 0.0063506}}, "normalized_score": 53.0}, {"_id": {"$oid": "69d4eb12b877594bc5718a90"}, "test_id": "T0067", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4.1", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-04-02\"],\"letter_title\":[\"Betrifft Schifffahrt Basel-Rheinfelden\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Basler Personenschiffahrtsgesellschaft\",\"Kur- und Verkehrsverein Rheinfelden\"]}}", "model": "gpt-4.1-2025-04-14", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 4909, "output_tokens": 86, "total_tokens": 4995, "input_cost_usd": 0.009818, "output_cost_usd": 0.000688, "estimated_cost_usd": 0.010506}, "duration": 6.854300498962402, "timestamp": "2026-01-24T12:30:03.063579", "parsed": {"metadata": {"send_date": ["1928-04-02"], "letter_title": ["Betrifft Schifffahrt Basel-Rheinfelden"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Basler Personenschiffahrtsgesellschaft", "Kur- und Verkehrsverein Rheinfelden"], "document_number": "letter22"}}, "conversation_id": "79dbfeda-e009-4921-b43e-2c5677e5f0de", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 2, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D1W80jWGAP1mJH9JQLjSJW7f9wE7I\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1928-04-02\\\"],\\n \\\"letter_title\\\": [\\\"Betrifft Schifffahrt Basel-Rheinfelden\\\"],\\n \\\"sender_persons\\\": [\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"],\\n \\\"receiver_persons\\\": [\\\"Basler Personenschiffahrtsgesellschaft\\\", \\\"Kur- und Verkehrsverein Rheinfelden\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-04-02\"],\"letter_title\":[\"Betrifft Schifffahrt Basel-Rheinfelden\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Basler Personenschiffahrtsgesellschaft\",\"Kur- und Verkehrsverein Rheinfelden\"]}}}}],\"created\":1769254200,\"model\":\"gpt-4.1-2025-04-14\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":\"fp_1a2c4a5ede\",\"usage\":{\"completion_tokens\":86,\"prompt_tokens\":4909,\"total_tokens\":4995,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.52, "f1_micro": 0.52, "cost_summary": {"total_input_tokens": 136163, "total_output_tokens": 3749, "total_tokens": 139912, "input_cost_usd": 0.2723260000000001, "output_cost_usd": 0.029992, "total_cost_usd": 0.30231799999999986}}, "normalized_score": 52.0}, {"_id": {"$oid": "69d4eb12b877594bc5718a91"}, "test_id": "T0071", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4.1-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. 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Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-05-15\"],\"letter_title\":[\"ABSCHRIFT\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"]}}", "model": "gpt-4.1-mini-2025-04-14", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 2875, "output_tokens": 46, "total_tokens": 2921, "cached_tokens": 1920, "input_cost_usd": 0.00115, "output_cost_usd": 7.36e-05, "estimated_cost_usd": 0.0012236}, "duration": 2.277175188064575, "timestamp": "2026-01-24T12:42:14.846873", "parsed": {"metadata": {"send_date": ["1928-05-15"], "letter_title": ["ABSCHRIFT"], "sender_persons": ["null"], "receiver_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "document_number": "letter36"}}, "conversation_id": "a8da838a-f8cc-486c-a46a-3008f8fa0266", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D1WJqVuvuj2hTZ2haFoZq98gZVsce\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1928-05-15\\\"],\\\"letter_title\\\":[\\\"ABSCHRIFT\\\"],\\\"sender_persons\\\":[\\\"null\\\"],\\\"receiver_persons\\\":[\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-05-15\"],\"letter_title\":[\"ABSCHRIFT\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"]}}}}],\"created\":1769254934,\"model\":\"gpt-4.1-mini-2025-04-14\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":\"fp_376a7ccef1\",\"usage\":{\"completion_tokens\":46,\"prompt_tokens\":2875,\"total_tokens\":2921,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":1920}}}"}, "scoring": {"f1_macro": 0.46, "f1_micro": 0.57, "cost_summary": {"total_input_tokens": 95735, "total_output_tokens": 1294, "total_tokens": 97029, "input_cost_usd": 0.03829399999999998, "output_cost_usd": 0.0020704, "total_cost_usd": 0.04036439999999999}}, "normalized_score": 46.0}, {"_id": {"$oid": "69d4eb12b877594bc5718a9b"}, "test_id": "T0198", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-flash", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1964-06-28\"],\"letter_title\":null,\"sender_persons\":[\"Max Vischer\"],\"receiver_persons\":[\"Herr Christ\"]}}", "model": "gemini-2.5-flash", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 852, "output_tokens": 47, "total_tokens": 1304, "input_cost_usd": 0.0002556, "output_cost_usd": 0.0001175, "estimated_cost_usd": 0.00037309999999999996}, "duration": 3.8805317878723145, "timestamp": "2026-01-24T13:00:25.352178", "parsed": {"metadata": {"send_date": ["1964-06-28"], "letter_title": null, "sender_persons": ["Max Vischer"], "receiver_persons": ["Herr Christ"], "document_number": "letter09"}}, "conversation_id": "1ae1082a-491e-4fc2-a6db-b01c001e0f58", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 1, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Sat, 24 Jan 2026 12:00:25 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=3595\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"video_metadata\":null,\"thought\":null,\"inline_data\":null,\"file_data\":null,\"thought_signature\":null,\"function_call\":null,\"code_execution_result\":null,\"executable_code\":null,\"function_response\":null,\"text\":\"{\\\"metadata\\\": {\\\"send_date\\\": [\\\"1964-06-28\\\"], \\\"letter_title\\\": null, \\\"sender_persons\\\": [\\\"Max Vischer\\\"], \\\"receiver_persons\\\": [\\\"Herr Christ\\\"]}}\"}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"url_context_metadata\":null,\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null}],\"create_time\":null,\"model_version\":\"gemini-2.5-flash\",\"prompt_feedback\":null,\"response_id\":\"WbR0acOJDt_m7M8PyIfh6AE\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":47,\"candidates_tokens_details\":null,\"prompt_token_count\":852,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":336},{\"modality\":\"IMAGE\",\"token_count\":516}],\"thoughts_token_count\":405,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":1304,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1964-06-28\"],\"letter_title\":null,\"sender_persons\":[\"Max Vischer\"],\"receiver_persons\":[\"Herr Christ\"]}}}"}, "scoring": {"f1_macro": 0.52, "f1_micro": 0.47, "cost_summary": {"total_input_tokens": 27006, "total_output_tokens": 2125, "total_tokens": 29131, "input_cost_usd": 0.008101799999999998, "output_cost_usd": 0.0053124999999999995, "total_cost_usd": 0.013414299999999999}}, "normalized_score": 52.0}, {"_id": {"$oid": "69d4eb12b877594bc5718a9d"}, "test_id": "T0042", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4o-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1935-08-17\"],\"letter_title\":[\"Basler Personenschifffahrtsgesellschaft\"],\"sender_persons\":[\"Basler Personenschifffahrtsgesellschaft\"],\"receiver_persons\":[\"Herr Fritz Ritter\"]}}", "model": "gpt-4o-mini-2024-07-18", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 37324, "output_tokens": 66, "total_tokens": 37390, "cached_tokens": 1280, "input_cost_usd": 0.0055986000000000005, "output_cost_usd": 3.96e-05, "estimated_cost_usd": 0.0056382}, "duration": 3.435582160949707, "timestamp": "2026-01-24T11:24:52.234767", "parsed": {"metadata": {"send_date": ["1935-08-17"], "letter_title": ["Basler Personenschifffahrtsgesellschaft"], "sender_persons": ["Basler Personenschifffahrtsgesellschaft"], "receiver_persons": ["Herr Fritz Ritter"], "document_number": "letter65"}}, "conversation_id": "38cb90b8-6d5a-442b-a312-a796c4e2cb94", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D1V6wylIlzCOo2wwRxvbXnd4IY7JI\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1935-08-17\\\"],\\n \\\"letter_title\\\": [\\\"Basler Personenschifffahrtsgesellschaft\\\"],\\n \\\"sender_persons\\\": [\\\"Basler Personenschifffahrtsgesellschaft\\\"],\\n \\\"receiver_persons\\\": [\\\"Herr Fritz Ritter\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1935-08-17\"],\"letter_title\":[\"Basler Personenschifffahrtsgesellschaft\"],\"sender_persons\":[\"Basler Personenschifffahrtsgesellschaft\"],\"receiver_persons\":[\"Herr Fritz Ritter\"]}}}}],\"created\":1769250290,\"model\":\"gpt-4o-mini-2024-07-18\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":\"fp_8bbc38b4db\",\"usage\":{\"completion_tokens\":66,\"prompt_tokens\":37324,\"total_tokens\":37390,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":1280}}}"}, "scoring": {"f1_macro": 0.44, "f1_micro": 0.52, "cost_summary": {"total_input_tokens": 1301450, "total_output_tokens": 1717, "total_tokens": 1303167, "input_cost_usd": 0.19521750000000004, "output_cost_usd": 0.0010302000000000002, "total_cost_usd": 0.1962477}}, "normalized_score": 44.0}, {"_id": {"$oid": "69d4eb12b877594bc5718aa0"}, "test_id": "T0205", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-flash-lite", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1938-04-23\"],\"letter_title\":[\"Basler Rheinschiffahrts-Aktiengesellschaft\"],\"sender_persons\":[\"Basler Rheinschiffahrts-Aktiengesellschaft\"],\"receiver_persons\":[\"Inhaber\"]}}", "model": "gemini-2.5-flash-lite", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 852, "output_tokens": 106, "total_tokens": 960, "input_cost_usd": 8.520000000000001e-05, "output_cost_usd": 4.24e-05, "estimated_cost_usd": 0.0001276}, "duration": 0.9622311592102051, "timestamp": "2026-01-24T13:34:58.828085", "parsed": {"metadata": {"send_date": ["1938-04-23"], "letter_title": ["Basler Rheinschiffahrts-Aktiengesellschaft"], "sender_persons": ["Basler Rheinschiffahrts-Aktiengesellschaft"], "receiver_persons": ["Inhaber"], "document_number": "letter26"}}, "conversation_id": "f3c23cb4-9a43-4e2a-ba7a-54368c8cbb74", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Sat, 24 Jan 2026 12:34:58 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=695\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"video_metadata\":null,\"thought\":null,\"inline_data\":null,\"file_data\":null,\"thought_signature\":null,\"function_call\":null,\"code_execution_result\":null,\"executable_code\":null,\"function_response\":null,\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1938-04-23\\\"\\n ],\\n \\\"letter_title\\\": [\\n \\\"Basler Rheinschiffahrts-Aktiengesellschaft\\\"\\n ],\\n \\\"sender_persons\\\": [\\n \\\"Basler Rheinschiffahrts-Aktiengesellschaft\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Inhaber\\\"\\n ]\\n }\\n}\"}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"url_context_metadata\":null,\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null}],\"create_time\":null,\"model_version\":\"gemini-2.5-flash-lite\",\"prompt_feedback\":null,\"response_id\":\"crx0aa7DL-DOnsEP-qP7-Ag\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":106,\"candidates_tokens_details\":null,\"prompt_token_count\":852,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":336},{\"modality\":\"IMAGE\",\"token_count\":516}],\"thoughts_token_count\":2,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":960,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1938-04-23\"],\"letter_title\":[\"Basler Rheinschiffahrts-Aktiengesellschaft\"],\"sender_persons\":[\"Basler Rheinschiffahrts-Aktiengesellschaft\"],\"receiver_persons\":[\"Inhaber\"]}}}"}, "scoring": {"f1_macro": 0.38, "f1_micro": 0.43, "cost_summary": {"total_input_tokens": 17430, "total_output_tokens": 2708, "total_tokens": 20138, "input_cost_usd": 0.0017430000000000006, "output_cost_usd": 0.0010831999999999999, "total_cost_usd": 0.0028262}}, "normalized_score": 38.0}, {"_id": {"$oid": "69d4eb12b877594bc5718aae"}, "test_id": "T0056", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.0-flash-lite", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-06-26\"],\"letter_title\":[\"Gesch\u00e4ftsleitung der Internationalen Ausstellung f\u00fcr Binnenschifffahrt und Wasserkraftnutzung\"],\"sender_persons\":[\"Basler Personenschifffahrtsgesellschaft\"],\"receiver_persons\":[\"Herrn O. Ritter\"]}}", "model": "gemini-2.0-flash-lite", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 1429, "output_tokens": 117, "total_tokens": 1546, "input_cost_usd": 0.00010717499999999999, "output_cost_usd": 3.51e-05, "estimated_cost_usd": 0.00014227499999999998}, "duration": 2.302935838699341, "timestamp": "2026-01-24T11:10:59.107642", "parsed": {"metadata": {"send_date": ["1926-06-26"], "letter_title": ["Gesch\u00e4ftsleitung der Internationalen Ausstellung f\u00fcr Binnenschifffahrt und Wasserkraftnutzung"], "sender_persons": ["Basler Personenschifffahrtsgesellschaft"], "receiver_persons": ["Herrn O. Ritter"], "document_number": "letter08"}}, "conversation_id": "5c57f30d-d086-4b51-9af7-ab67f679bb55", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Sat, 24 Jan 2026 10:10:59 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=1715\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"video_metadata\":null,\"thought\":null,\"inline_data\":null,\"file_data\":null,\"thought_signature\":null,\"function_call\":null,\"code_execution_result\":null,\"executable_code\":null,\"function_response\":null,\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1926-06-26\\\"\\n ],\\n \\\"letter_title\\\": [\\n \\\"Gesch\u00e4ftsleitung der Internationalen Ausstellung f\u00fcr Binnenschifffahrt und Wasserkraftnutzung\\\"\\n ],\\n \\\"sender_persons\\\": [\\n \\\"Basler Personenschifffahrtsgesellschaft\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Herrn O. 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Ritter\"]}}}"}, "scoring": {"f1_macro": 0.45, "f1_micro": 0.56, "cost_summary": {"total_input_tokens": 46819, "total_output_tokens": 2423, "total_tokens": 49242, "input_cost_usd": 0.003511425000000001, "output_cost_usd": 0.0007268999999999999, "total_cost_usd": 0.004238325}}, "normalized_score": 45.0}, {"_id": {"$oid": "69d4eb12b877594bc5718ab7"}, "test_id": "T0039", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4o", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-09-07\"],\"letter_title\":[\"Betr.Personenschiffahrt\"],\"sender_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft\"],\"receiver_persons\":[\"Dr. W. 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Vischer-von Planta"], "document_number": "letter48"}}, "conversation_id": "19a42c2d-4ae2-44d0-8e84-8bdd785fb6ec", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"chatcmpl-D1V4VQ9Nn0H6A8sgWACrlKNKTiJID\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1932-09-07\\\"],\\\"letter_title\\\":[\\\"Betr.Personenschiffahrt\\\"],\\\"sender_persons\\\":[\\\"Basler Rheinschiffahrt Aktiengesellschaft\\\"],\\\"receiver_persons\\\":[\\\"Dr. W. 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You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1940-06-25\"],\"letter_title\":[\"Letter from the Swiss Federal Council\"],\"sender_persons\":[\"Swiss Federal Council\"],\"receiver_persons\":[\"Reich Minister of Public Enlightenment and Propaganda\"]}}", "model": "mistral-medium-2505", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 70, "total_tokens": 655, "input_cost_usd": 0.00023400000000000002, "output_cost_usd": 0.00014, "estimated_cost_usd": 0.000374}, "duration": 1.208414077758789, "timestamp": "2026-01-24T11:40:36.403453", "parsed": {"metadata": {"letter_title": ["Letter from the Swiss Federal Council"], "send_date": ["1940-06-25"], "sender_persons": ["Swiss Federal Council"], "receiver_persons": ["Reich Minister of Public Enlightenment and Propaganda"], "document_number": "letter12"}}, "conversation_id": "51f5a181-2547-4bee-8534-7baa3d1b0c18", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"a9cf0c2ba7464743a2525e103ff73553\",\"object\":\"chat.completion\",\"model\":\"mistral-medium-2505\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":70,\"total_tokens\":655,\"num_cached_tokens\":576},\"created\":1769251235,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [\\\"Letter from the Swiss Federal Council\\\"],\\n \\\"send_date\\\": [\\\"1940-06-25\\\"],\\n \\\"sender_persons\\\": [\\\"Swiss Federal Council\\\"],\\n \\\"receiver_persons\\\": [\\\"Reich Minister of Public Enlightenment and Propaganda\\\"]\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 33345, "total_output_tokens": 3764, "total_tokens": 37109, "input_cost_usd": 0.013337999999999992, "output_cost_usd": 0.007528000000000002, "total_cost_usd": 0.020866000000000003}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718aba"}, "test_id": "T0213", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-flash-lite-preview-09-2025", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". 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Krasting\\\"\\n ]\\n }\\n}\"}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"url_context_metadata\":null,\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null}],\"create_time\":null,\"model_version\":\"gemini-2.5-flash-lite-preview-09-2025\",\"prompt_feedback\":null,\"response_id\":\"bMB0aZmPBcDl7M8P5IuNgAI\",\"usage_metadata\":{\"cache_tokens_details\":[{\"modality\":\"IMAGE\",\"token_count\":202},{\"modality\":\"TEXT\",\"token_count\":264}],\"cached_content_token_count\":466,\"candidates_token_count\":112,\"candidates_tokens_details\":null,\"prompt_token_count\":594,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":336},{\"modality\":\"IMAGE\",\"token_count\":258}],\"thoughts_token_count\":2,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":708,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1926-03-29\"],\"letter_title\":[\"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"Herrn Dr. W. Krasting\"]}}}"}, "scoring": {"f1_macro": 0.37, "f1_micro": 0.45, "cost_summary": {"total_input_tokens": 17430, "total_output_tokens": 2734, "total_tokens": 20164, "input_cost_usd": 0.0017430000000000006, "output_cost_usd": 0.0010936000000000001, "total_cost_usd": 0.0028366}}, "normalized_score": 37.0}, {"_id": {"$oid": "69d4eb12b877594bc5718abf"}, "test_id": "T0038", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4o", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1935-08-15\"],\"letter_title\":null,\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrts A.-G.\"]}}", "model": "gpt-4o-2024-08-06", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 1594, "output_tokens": 51, "total_tokens": 1645, "input_cost_usd": 0.003985, "output_cost_usd": 0.00051, "estimated_cost_usd": 0.004495}, "duration": 3.0634515285491943, "timestamp": "2026-01-24T11:20:20.306373", "parsed": {"metadata": {"send_date": ["1935-08-15"], "letter_title": null, "sender_persons": ["Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["Basler Rheinschiffahrts A.-G."], "document_number": "letter63"}}, "conversation_id": "b9150708-b592-4c81-8055-8c7014a3e4bc", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D1V2YKGHH4T2VutXDorEYQwxtFdlx\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1935-08-15\\\"],\\\"letter_title\\\":null,\\\"sender_persons\\\":[\\\"Basler Personenschiffahrtsgesellschaft\\\"],\\\"receiver_persons\\\":[\\\"Basler Rheinschiffahrts A.-G.\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1935-08-15\"],\"letter_title\":null,\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrts A.-G.\"]}}}}],\"created\":1769250018,\"model\":\"gpt-4o-2024-08-06\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":\"fp_a0e9480a2f\",\"usage\":{\"completion_tokens\":51,\"prompt_tokens\":1594,\"total_tokens\":1645,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.44, "f1_micro": 0.55, "cost_summary": {"total_input_tokens": 50900, "total_output_tokens": 1141, "total_tokens": 52041, "input_cost_usd": 0.12725000000000003, "output_cost_usd": 0.01141, "total_cost_usd": 0.13866}}, "normalized_score": 44.0}, {"_id": {"$oid": "69d4eb12b877594bc5718ac8"}, "test_id": "T0103", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-sonnet-4-20250514", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-02-27\"],\"letter_title\":null,\"sender_persons\":[\"\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.-G.\"]}}", "model": "claude-sonnet-4-20250514", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 2514, "output_tokens": 94, "total_tokens": 2608, "input_cost_usd": 0.007542, "output_cost_usd": 0.00141, "estimated_cost_usd": 0.008952}, "duration": 3.751556634902954, "timestamp": "2026-01-24T11:24:20.918044", "parsed": {"metadata": {"letter_title": null, "send_date": ["1928-02-27"], "sender_persons": [""], "receiver_persons": ["Basler Rheinschiffahrt A.-G."], "document_number": "letter16"}}, "conversation_id": "d66812e1-f5a4-44e1-8d17-e0c0be677bfc", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"msg_01QEzG6X7Ts8WuAxANkhMzxi\",\"content\":[{\"id\":\"toolu_018wnyM4jHmh7RMDwRZsvDvB\",\"input\":{\"metadata\":{\"letter_title\":null,\"send_date\":[\"1928-02-27\"],\"sender_persons\":[\"\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.-G.\"],\"document_number\":\"letter16\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\"}],\"model\":\"claude-sonnet-4-20250514\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"input_tokens\":2514,\"output_tokens\":94,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.42, "f1_micro": 0.41, "cost_summary": {"total_input_tokens": 207012, "total_output_tokens": 5900, "total_tokens": 212912, "input_cost_usd": 0.6210360000000003, "output_cost_usd": 0.08850000000000002, "total_cost_usd": 0.7095360000000002}}, "normalized_score": 42.0}, {"_id": {"$oid": "69d4eb12b877594bc5718ad2"}, "test_id": "T0044", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.0-flash", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-03-24\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.-G.\"]}}", "model": "gemini-2.0-flash", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 913, "output_tokens": 76, "total_tokens": 989, "input_cost_usd": 9.13e-05, "output_cost_usd": 3.0400000000000004e-05, "estimated_cost_usd": 0.0001217}, "duration": 1.7313995361328125, "timestamp": "2026-01-24T11:09:18.370128", "parsed": {"metadata": {"send_date": ["1928-03-24"], "letter_title": ["null"], "sender_persons": ["Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["Basler Rheinschiffahrt A.-G."], "document_number": "letter20"}}, "conversation_id": "9fda7ca7-3624-4d21-a0bd-23e0614b6d89", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Sat, 24 Jan 2026 10:09:18 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=1446\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"video_metadata\":null,\"thought\":null,\"inline_data\":null,\"file_data\":null,\"thought_signature\":null,\"function_call\":null,\"code_execution_result\":null,\"executable_code\":null,\"function_response\":null,\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1928-03-24\\\"],\\n \\\"letter_title\\\": [\\\"null\\\"],\\n \\\"sender_persons\\\": [\\\"Basler Personenschiffahrtsgesellschaft\\\"],\\n \\\"receiver_persons\\\": [\\\"Basler Rheinschiffahrt A.-G.\\\"]\\n }\\n}\"}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"url_context_metadata\":null,\"avg_logprobs\":-0.0276990156424673,\"grounding_metadata\":null,\"index\":null,\"logprobs_result\":null,\"safety_ratings\":null}],\"create_time\":null,\"model_version\":\"gemini-2.0-flash\",\"prompt_feedback\":null,\"response_id\":\"TZp0aeJps-Tszw-Gm_7gAg\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":76,\"candidates_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":76}],\"prompt_token_count\":913,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":397},{\"modality\":\"IMAGE\",\"token_count\":516}],\"thoughts_token_count\":null,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":989,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1928-03-24\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.-G.\"]}}}"}, "scoring": {"f1_macro": 0.48, "f1_micro": 0.57, "cost_summary": {"total_input_tokens": 46819, "total_output_tokens": 2171, "total_tokens": 48990, "input_cost_usd": 0.004681899999999999, "output_cost_usd": 0.0008684, "total_cost_usd": 0.0055503}}, "normalized_score": 48.0}, {"_id": {"$oid": "69d4eb12b877594bc5718ad5"}, "test_id": "T0524", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-haiku-4-5-20251001", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-04-02\"],\"letter_title\":[\"Betrifft Schiffahrt Basel-Rheinfelden\"],\"sender_persons\":[\"Basler Rheinschifffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Kur- und Verkehrsverein, Rheinfelden\"]}}", "model": "claude-haiku-4-5-20251001", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 7449, "output_tokens": 124, "total_tokens": 7573, "input_cost_usd": 0.007449, "output_cost_usd": 0.00062, "estimated_cost_usd": 0.008069}, "duration": 2.9511866569519043, "timestamp": "2026-01-24T17:47:55.704726", "parsed": {"metadata": {"letter_title": ["Betrifft Schiffahrt Basel-Rheinfelden"], "send_date": ["1928-04-02"], "sender_persons": ["Basler Rheinschifffahrt-Aktiengesellschaft"], "receiver_persons": ["Kur- und Verkehrsverein, Rheinfelden"], "document_number": "letter22"}}, "conversation_id": "519e07b3-6091-454f-8f62-7de3f1933bdf", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"msg_01XPxXPXNGqd5CPiN1KFVPuA\",\"content\":[{\"id\":\"toolu_01Av1SGUizebRedybrrVeY1Q\",\"input\":{\"metadata\":{\"letter_title\":[\"Betrifft Schiffahrt Basel-Rheinfelden\"],\"send_date\":[\"1928-04-02\"],\"sender_persons\":[\"Basler Rheinschifffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Kur- und Verkehrsverein, Rheinfelden\"],\"document_number\":\"letter22\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\"}],\"model\":\"claude-haiku-4-5-20251001\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"input_tokens\":7449,\"output_tokens\":124,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.45, "f1_micro": 0.42, "cost_summary": {"total_input_tokens": 137358, "total_output_tokens": 3365, "total_tokens": 140723, "input_cost_usd": 0.137358, "output_cost_usd": 0.016825, "total_cost_usd": 0.154183}}, "normalized_score": 45.0}, {"_id": {"$oid": "69d4eb12b877594bc5718ad8"}, "test_id": "T0197", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-flash", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1933-04-04\"],\"letter_title\":null,\"sender_persons\":[\"BASLER PERSONENSCHIFFFAHRTSGESELLSCHAFT\"],\"receiver_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"]}}", "model": "gemini-2.5-flash", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 852, "output_tokens": 82, "total_tokens": 2822, "input_cost_usd": 0.0002556, "output_cost_usd": 0.000205, "estimated_cost_usd": 0.0004606}, "duration": 9.155715942382812, "timestamp": "2026-01-24T12:58:56.889596", "parsed": {"metadata": {"send_date": ["1933-04-04"], "letter_title": null, "sender_persons": ["BASLER PERSONENSCHIFFFAHRTSGESELLSCHAFT"], "receiver_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "document_number": "letter24"}}, "conversation_id": "4890b282-c747-43f4-baea-6a98a84525ec", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Sat, 24 Jan 2026 11:58:56 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=8874\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"video_metadata\":null,\"thought\":null,\"inline_data\":null,\"file_data\":null,\"thought_signature\":null,\"function_call\":null,\"code_execution_result\":null,\"executable_code\":null,\"function_response\":null,\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1933-04-04\\\"],\\n \\\"letter_title\\\": null,\\n \\\"sender_persons\\\": [\\\"BASLER PERSONENSCHIFFFAHRTSGESELLSCHAFT\\\"],\\n \\\"receiver_persons\\\": [\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"]\\n }\\n}\"}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"url_context_metadata\":null,\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null}],\"create_time\":null,\"model_version\":\"gemini-2.5-flash\",\"prompt_feedback\":null,\"response_id\":\"ALR0af3_MdzskdUPoNHsgQY\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":82,\"candidates_tokens_details\":null,\"prompt_token_count\":852,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":336},{\"modality\":\"IMAGE\",\"token_count\":516}],\"thoughts_token_count\":1888,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":2822,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1933-04-04\"],\"letter_title\":null,\"sender_persons\":[\"BASLER PERSONENSCHIFFFAHRTSGESELLSCHAFT\"],\"receiver_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"]}}}"}, "scoring": {"f1_macro": 0.5, "f1_micro": 0.57, "cost_summary": {"total_input_tokens": 17430, "total_output_tokens": 1585, "total_tokens": 19015, "input_cost_usd": 0.005228999999999998, "output_cost_usd": 0.0039625, "total_cost_usd": 0.0091915}}, "normalized_score": 50.0}, {"_id": {"$oid": "69d4eb12b877594bc5718ada"}, "test_id": "T0126", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-pro", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1935-08-16\"],\"letter_title\":null,\"sender_persons\":[\"Basler Rheinschifffahrt Aktiengesellschaft\"],\"receiver_persons\":[\"Basler Personenschifffahrts-Gesellschaft\"]}}", "model": "gemini-2.5-pro", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 594, "output_tokens": 96, "total_tokens": 1118, "input_cost_usd": 0.0007425, "output_cost_usd": 0.00096, "estimated_cost_usd": 0.0017025}, "duration": 5.1991987228393555, "timestamp": "2026-01-24T11:30:48.268975", "parsed": {"metadata": {"send_date": ["1935-08-16"], "letter_title": null, "sender_persons": ["Basler Rheinschifffahrt Aktiengesellschaft"], "receiver_persons": ["Basler Personenschifffahrts-Gesellschaft"], "document_number": "letter64"}}, "conversation_id": "a95d762a-da8a-43b1-9430-cb01ff0138de", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Sat, 24 Jan 2026 10:30:48 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=5038\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"video_metadata\":null,\"thought\":null,\"inline_data\":null,\"file_data\":null,\"thought_signature\":null,\"function_call\":null,\"code_execution_result\":null,\"executable_code\":null,\"function_response\":null,\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1935-08-16\\\"\\n ],\\n \\\"letter_title\\\": null,\\n \\\"sender_persons\\\": [\\n \\\"Basler Rheinschifffahrt Aktiengesellschaft\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Basler Personenschifffahrts-Gesellschaft\\\"\\n ]\\n }\\n}\"}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"url_context_metadata\":null,\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null}],\"create_time\":null,\"model_version\":\"gemini-2.5-pro\",\"prompt_feedback\":null,\"response_id\":\"WJ90ac6nCrPk7M8Phpv-4AI\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":96,\"candidates_tokens_details\":null,\"prompt_token_count\":594,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":336},{\"modality\":\"IMAGE\",\"token_count\":258}],\"thoughts_token_count\":428,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":1118,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1935-08-16\"],\"letter_title\":null,\"sender_persons\":[\"Basler Rheinschifffahrt Aktiengesellschaft\"],\"receiver_persons\":[\"Basler Personenschifffahrts-Gesellschaft\"]}}}"}, "scoring": {"f1_macro": 0.56, "f1_micro": 0.5, "cost_summary": {"total_input_tokens": 27006, "total_output_tokens": 3214, "total_tokens": 30220, "input_cost_usd": 0.0337575, "output_cost_usd": 0.03214, "total_cost_usd": 0.06589750000000001}}, "normalized_score": 56.00000000000001}, {"_id": {"$oid": "69d4eb12b877594bc5718ae0"}, "test_id": "T0254", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "qwen/qwen3-vl-30b-a3b-instruct", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-03-26\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"W. W. Mann\"],\"receiver_persons\":[\"Herrn Christ c/o. Paravicini, Christ & Co.\"]}}", "model": "qwen/qwen3-vl-30b-a3b-instruct", "provider": "openrouter", "finish_reason": "stop", "usage": {"input_tokens": 3208, "output_tokens": 71, "total_tokens": 3279, "input_cost_usd": 0.0004812, "output_cost_usd": 4.26e-05, "estimated_cost_usd": 0.0005237999999999999}, "duration": 2.661968469619751, "timestamp": "2026-01-24T23:03:00.062670", "parsed": {"metadata": {"send_date": ["1926-03-26"], "letter_title": ["null"], "sender_persons": ["W. W. Mann"], "receiver_persons": ["Herrn Christ c/o. Paravicini, Christ & Co."], "document_number": "letter04"}}, "conversation_id": "84f2bdee-d262-439e-a594-5143e179d7c7", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"gen-1769292177-Rj2WF64zIBbljr7q0rZf\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1926-03-26\\\"],\\n \\\"letter_title\\\": [\\\"null\\\"],\\n \\\"sender_persons\\\": [\\\"W. W. Mann\\\"],\\n \\\"receiver_persons\\\": [\\\"Herrn Christ c/o. Paravicini, Christ & Co.\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1926-03-26\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"W. W. Mann\"],\"receiver_persons\":[\"Herrn Christ c/o. Paravicini, Christ & Co.\"]}},\"reasoning\":null},\"native_finish_reason\":\"stop\"}],\"created\":1769292177,\"model\":\"qwen/qwen3-vl-30b-a3b-instruct\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":71,\"prompt_tokens\":3208,\"total_tokens\":3279,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":null,\"image_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0,\"video_tokens\":0},\"cost\":0.0006913,\"is_byok\":false,\"cost_details\":{\"upstream_inference_cost\":null,\"upstream_inference_prompt_cost\":0.0006416,\"upstream_inference_completions_cost\":0.0000497}},\"provider\":\"Phala\"}"}, "scoring": {"f1_macro": 0.48, "f1_micro": 0.49, "cost_summary": {"total_input_tokens": 296530, "total_output_tokens": 4606, "total_tokens": 301136, "input_cost_usd": 0.04447950000000003, "output_cost_usd": 0.0027635999999999993, "total_cost_usd": 0.04724309999999999}}, "normalized_score": 48.0}, {"_id": {"$oid": "69d4eb12b877594bc5718ae1"}, "test_id": "T0189", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-large-2411", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":null,\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":null}}", "model": "mistral-large-2411", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 640, "output_tokens": 51, "total_tokens": 691, "input_cost_usd": 0.00128, "output_cost_usd": 0.000306, "estimated_cost_usd": 0.0015860000000000002}, "duration": 1.2060470581054688, "timestamp": "2026-01-24T11:59:00.386259", "parsed": {"metadata": {"letter_title": null, "send_date": null, "sender_persons": null, "receiver_persons": null, "document_number": "letter61"}}, "conversation_id": "e39669a8-4cae-49ac-a731-be889f8a6ed9", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"6e01519d8a104952b1632da0967fe780\",\"object\":\"chat.completion\",\"model\":\"mistral-large-2411\",\"usage\":{\"prompt_tokens\":640,\"completion_tokens\":51,\"total_tokens\":691,\"num_cached_tokens\":640},\"created\":1769252339,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"send_date\\\": null,\\n \\\"sender_persons\\\": null,\\n \\\"receiver_persons\\\": null\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 16000, "total_output_tokens": 1259, "total_tokens": 17259, "input_cost_usd": 0.032, "output_cost_usd": 0.007553999999999999, "total_cost_usd": 0.03955399999999999}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718ae2"}, "test_id": "T0438", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-small-2506", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"null\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"null\"]}}", "model": "mistral-small-2506", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 46, "total_tokens": 631, "input_cost_usd": 5.8500000000000006e-05, "output_cost_usd": 1.38e-05, "estimated_cost_usd": 7.230000000000001e-05}, "duration": 1.3575372695922852, "timestamp": "2026-01-24T13:17:57.145992", "parsed": {"metadata": {"letter_title": ["null"], "send_date": ["null"], "sender_persons": ["null"], "receiver_persons": ["null"], "document_number": "letter02"}}, "conversation_id": "b126b2b1-0998-4e0d-8c56-7c22c73e00e9", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"89b00851a25348c6abb1bef1deff6df3\",\"object\":\"chat.completion\",\"model\":\"mistral-small-2506\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":46,\"total_tokens\":631,\"num_cached_tokens\":576},\"created\":1769257076,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [\\\"null\\\"],\\n \\\"send_date\\\": [\\\"null\\\"],\\n \\\"sender_persons\\\": [\\\"null\\\"],\\n \\\"receiver_persons\\\": [\\\"null\\\"]\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 18720, "total_output_tokens": 1396, "total_tokens": 20116, "input_cost_usd": 0.001871999999999999, "output_cost_usd": 0.00041879999999999993, "total_cost_usd": 0.0022908}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718af1"}, "test_id": "T0105", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-sonnet-4-20250514", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-04-04\"],\"letter_title\":[\"Betrifft Kauf \\\"Rheinfelden\\\"\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Basler Personenschiffahrtsgesellschaft\"]}}", "model": "claude-sonnet-4-20250514", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 4068, "output_tokens": 119, "total_tokens": 4187, "input_cost_usd": 0.012204, "output_cost_usd": 0.0017850000000000001, "estimated_cost_usd": 0.013989}, "duration": 4.243444204330444, "timestamp": "2026-01-24T11:29:38.492745", "parsed": {"metadata": {"letter_title": ["Betrifft Kauf \"Rheinfelden\""], "send_date": ["1928-04-04"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Basler Personenschiffahrtsgesellschaft"], "document_number": "letter25"}}, "conversation_id": "aeb4165f-c7d5-4c9e-8ffb-b4458059fa27", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"msg_01FxJoetsUfaNXzwpFUdoc8q\",\"content\":[{\"id\":\"toolu_01HZvTDLhTTzzZKEr7LVq4Ay\",\"input\":{\"metadata\":{\"letter_title\":[\"Betrifft Kauf \\\"Rheinfelden\\\"\"],\"send_date\":[\"1928-04-04\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"document_number\":\"letter25\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\"}],\"model\":\"claude-sonnet-4-20250514\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"input_tokens\":4068,\"output_tokens\":119,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.47, "f1_micro": 0.43, "cost_summary": {"total_input_tokens": 128622, "total_output_tokens": 3378, "total_tokens": 132000, "input_cost_usd": 0.3858659999999998, "output_cost_usd": 0.05067, "total_cost_usd": 0.4365360000000001}}, "normalized_score": 47.0}, {"_id": {"$oid": "69d4eb12b877594bc5718af2"}, "test_id": "T0437", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-small-2506", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"null\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"null\"]}}", "model": "mistral-small-2506", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 46, "total_tokens": 631, "input_cost_usd": 5.8500000000000006e-05, "output_cost_usd": 1.38e-05, "estimated_cost_usd": 7.230000000000001e-05}, "duration": 1.4229209423065186, "timestamp": "2026-01-24T13:17:50.798425", "parsed": {"metadata": {"letter_title": ["null"], "sender_persons": ["null"], "send_date": ["null"], "receiver_persons": ["null"], "document_number": "letter49"}}, "conversation_id": "72c21172-541e-4c4f-a037-01bcc9137939", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"a923135a6a30463d838edad03735f298\",\"object\":\"chat.completion\",\"model\":\"mistral-small-2506\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":46,\"total_tokens\":631,\"num_cached_tokens\":576},\"created\":1769257069,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [\\\"null\\\"],\\n \\\"sender_persons\\\": [\\\"null\\\"],\\n \\\"send_date\\\": [\\\"null\\\"],\\n \\\"receiver_persons\\\": [\\\"null\\\"]\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 14625, "total_output_tokens": 1118, "total_tokens": 15743, "input_cost_usd": 0.0014624999999999994, "output_cost_usd": 0.0003354000000000001, "total_cost_usd": 0.0017978999999999996}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718af4"}, "test_id": "T0075", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4.1-nano", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-02-16\"],\"letter_title\":[\"Schiffbau- und Schifffahrts-Planung\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Herr Christ\"]}}", "model": "gpt-4.1-nano-2025-04-14", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 11358, "output_tokens": 57, "total_tokens": 11415, "cached_tokens": 4864, "input_cost_usd": 0.0011358, "output_cost_usd": 2.2800000000000002e-05, "estimated_cost_usd": 0.0011585999999999999}, "duration": 4.306396245956421, "timestamp": "2026-01-24T12:49:13.426541", "parsed": {"metadata": {"send_date": ["1926-02-16"], "letter_title": ["Schiffbau- und Schifffahrts-Planung"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Herr Christ"], "document_number": "letter01"}}, "conversation_id": "4030f504-81f5-4ff6-a866-672c235bfe09", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D1WQacABZU6OcywX3gmZwT3kxOFAb\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1926-02-16\\\"],\\\"letter_title\\\":[\\\"Schiffbau- und Schifffahrts-Planung\\\"],\\\"sender_persons\\\":[\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"],\\\"receiver_persons\\\":[\\\"Herr Christ\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1926-02-16\"],\"letter_title\":[\"Schiffbau- und Schifffahrts-Planung\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Herr Christ\"]}}}}],\"created\":1769255352,\"model\":\"gpt-4.1-nano-2025-04-14\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":\"fp_2b9b3207a6\",\"usage\":{\"completion_tokens\":57,\"prompt_tokens\":11358,\"total_tokens\":11415,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":4864}}}"}, "scoring": {"f1_macro": 0.52, "f1_micro": 0.47, "cost_summary": {"total_input_tokens": 243897, "total_output_tokens": 1848, "total_tokens": 245745, "input_cost_usd": 0.024389700000000004, "output_cost_usd": 0.0007392000000000001, "total_cost_usd": 0.025128899999999992}}, "normalized_score": 52.0}, {"_id": {"$oid": "69d4eb12b877594bc5718afb"}, "test_id": "T0020", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.0-flash-lite", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1933-07-04\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"Ing. Dr. W. Wacker\",\"Ing. Arthur Oettinger\"],\"receiver_persons\":[\"An die Basler Rheinschifffahrts A.-G.\"]}}", "model": "gemini-2.0-flash-lite", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 913, "output_tokens": 114, "total_tokens": 1027, "input_cost_usd": 6.8475e-05, "output_cost_usd": 3.42e-05, "estimated_cost_usd": 0.00010267499999999999}, "duration": 1.9399166107177734, "timestamp": "2026-01-24T11:07:40.183701", "parsed": {"metadata": {"send_date": ["1933-07-04"], "letter_title": ["null"], "sender_persons": ["Ing. Dr. W. Wacker", "Ing. Arthur Oettinger"], "receiver_persons": ["An die Basler Rheinschifffahrts A.-G."], "document_number": "letter62"}}, "conversation_id": "7894d888-cc7b-4aa6-88ac-177486379c7b", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 2, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Sat, 24 Jan 2026 10:07:40 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=1600\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"video_metadata\":null,\"thought\":null,\"inline_data\":null,\"file_data\":null,\"thought_signature\":null,\"function_call\":null,\"code_execution_result\":null,\"executable_code\":null,\"function_response\":null,\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1933-07-04\\\"\\n ],\\n \\\"letter_title\\\": [\\n \\\"null\\\"\\n ],\\n \\\"sender_persons\\\": [\\n \\\"Ing. Dr. W. Wacker\\\",\\n \\\"Ing. 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You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". 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Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1988-07-14\"],\"letter_title\":null,\"sender_persons\":[\"Basler Personenschifffahrtsgesellschaft\"],\"receiver_persons\":[\"Redaktion der Basler Nachrichten\"]}}", "model": "claude-opus-4-1-20250805", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 2514, "output_tokens": 104, "total_tokens": 2618, "input_cost_usd": 0.03771, "output_cost_usd": 0.0078, "estimated_cost_usd": 0.04551}, "duration": 4.90143895149231, "timestamp": "2026-01-24T11:40:52.100424", "parsed": {"metadata": {"letter_title": null, "send_date": ["1988-07-14"], "sender_persons": ["Basler Personenschifffahrtsgesellschaft"], "receiver_persons": ["Redaktion der Basler Nachrichten"], "document_number": "letter11"}}, "conversation_id": "11812213-2c75-464d-8cf1-9658ef1ea863", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"msg_01Mce59YdUhu34WGhWrPyFFh\",\"content\":[{\"id\":\"toolu_018sEUGCbNrFVTPhGjczXFgD\",\"input\":{\"metadata\":{\"letter_title\":null,\"send_date\":[\"1988-07-14\"],\"sender_persons\":[\"Basler Personenschifffahrtsgesellschaft\"],\"receiver_persons\":[\"Redaktion der Basler Nachrichten\"],\"document_number\":\"letter11\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\"}],\"model\":\"claude-opus-4-1-20250805\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"input_tokens\":2514,\"output_tokens\":104,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.44, "f1_micro": 0.51, "cost_summary": {"total_input_tokens": 78390, "total_output_tokens": 2557, "total_tokens": 80947, "input_cost_usd": 1.1758499999999996, "output_cost_usd": 0.19177500000000006, "total_cost_usd": 1.3676249999999999}}, "normalized_score": 44.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b0a"}, "test_id": "T0074", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4.1-nano", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-08-13\"],\"letter_title\":[\"Abschrift\"],\"sender_persons\":[\"J. A. Ritter\"],\"receiver_persons\":[\"Herrn Dr. Max Vischer\"]}}", "model": "gpt-4.1-nano-2025-04-14", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 11358, "output_tokens": 49, "total_tokens": 11407, "cached_tokens": 4864, "input_cost_usd": 0.0011358, "output_cost_usd": 1.9600000000000002e-05, "estimated_cost_usd": 0.0011554}, "duration": 3.6371943950653076, "timestamp": "2026-01-24T12:48:19.056707", "parsed": {"metadata": {"send_date": ["1926-08-13"], "letter_title": ["Abschrift"], "sender_persons": ["J. A. Ritter"], "receiver_persons": ["Herrn Dr. Max Vischer"], "document_number": "letter12"}}, "conversation_id": "8d0fb707-5b8e-412d-8aab-0e2d635217bf", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D1WPiF9DIzxpL42tmK3Rsbe8kYUe9\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1926-08-13\\\"],\\\"letter_title\\\": [\\\"Abschrift\\\"],\\\"sender_persons\\\": [\\\"J. A. Ritter\\\"],\\\"receiver_persons\\\": [\\\"Herrn Dr. Max Vischer\\\"]}} \",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1926-08-13\"],\"letter_title\":[\"Abschrift\"],\"sender_persons\":[\"J. A. 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Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-12-19\"],\"letter_title\":[\"Betr.Personenschiffahrt\"],\"sender_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft\"],\"receiver_persons\":[\"Dr.H.Vischer - von Planta\"]}}", "model": "claude-sonnet-4-5-20250929", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 2787, "output_tokens": 114, "total_tokens": 2901, "input_cost_usd": 0.008361, "output_cost_usd": 0.0017100000000000001, "estimated_cost_usd": 0.010071}, "duration": 3.5477588176727295, "timestamp": "2026-01-24T14:00:55.614441", "parsed": {"metadata": {"letter_title": ["Betr.Personenschiffahrt"], "send_date": ["1932-12-19"], "sender_persons": ["Basler Rheinschiffahrt Aktiengesellschaft"], "receiver_persons": ["Dr.H.Vischer - von Planta"], "document_number": "letter60"}}, "conversation_id": "d3ddaa2e-56bb-4ded-9e8a-c87e7db30ec3", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"msg_01554emUZUG94yZkxm8Rbz4M\",\"content\":[{\"id\":\"toolu_01BYqnGBs2GJv4Uga9C1heZM\",\"input\":{\"metadata\":{\"letter_title\":[\"Betr.Personenschiffahrt\"],\"send_date\":[\"1932-12-19\"],\"sender_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft\"],\"receiver_persons\":[\"Dr.H.Vischer - von Planta\"],\"document_number\":\"letter60\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\"}],\"model\":\"claude-sonnet-4-5-20250929\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"input_tokens\":2787,\"output_tokens\":114,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.49, "f1_micro": 0.45, "cost_summary": {"total_input_tokens": 137358, "total_output_tokens": 3294, "total_tokens": 140652, "input_cost_usd": 0.41207400000000016, "output_cost_usd": 0.049409999999999996, "total_cost_usd": 0.46148399999999995}}, "normalized_score": 49.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b12"}, "test_id": "T0076", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4o-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-03-26\"],\"letter_title\":[\"An die Basler Rheinschiffahrt A.-G.\"],\"sender_persons\":[\"Basler Personenschifffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.-G.\"]}}", "model": "gpt-4o-mini-2024-07-18", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 37324, "output_tokens": 77, "total_tokens": 37401, "input_cost_usd": 0.0055986000000000005, "output_cost_usd": 4.62e-05, "estimated_cost_usd": 0.0056448}, "duration": 3.8046202659606934, "timestamp": "2026-01-24T12:52:56.966889", "parsed": {"metadata": {"send_date": ["1928-03-26"], "letter_title": ["An die Basler Rheinschiffahrt A.-G."], "sender_persons": ["Basler Personenschifffahrtsgesellschaft"], "receiver_persons": ["Basler Rheinschiffahrt A.-G."], "document_number": "letter21"}}, "conversation_id": "eeb13fb9-df4e-4f61-9614-62042a347342", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D1WUAikTRZFPe02lMvIRn3cwhVgP9\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1928-03-26\\\"],\\n \\\"letter_title\\\": [\\\"An die Basler Rheinschiffahrt A.-G.\\\"],\\n \\\"sender_persons\\\": [\\\"Basler Personenschifffahrtsgesellschaft\\\"],\\n \\\"receiver_persons\\\": [\\\"Basler Rheinschiffahrt A.-G.\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-03-26\"],\"letter_title\":[\"An die Basler Rheinschiffahrt A.-G.\"],\"sender_persons\":[\"Basler Personenschifffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.-G.\"]}}}}],\"created\":1769255574,\"model\":\"gpt-4o-mini-2024-07-18\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":\"fp_8bbc38b4db\",\"usage\":{\"completion_tokens\":77,\"prompt_tokens\":37324,\"total_tokens\":37401,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.49, "f1_micro": 0.5, "cost_summary": {"total_input_tokens": 3637703, "total_output_tokens": 3954, "total_tokens": 3641657, "input_cost_usd": 0.5456554500000002, "output_cost_usd": 0.0023723999999999993, "total_cost_usd": 0.54802785}}, "normalized_score": 49.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b18"}, "test_id": "T0173", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-medium-2508", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1920-07-24\"],\"letter_title\":[\"Letter from the Swiss Federal Council to the United Nations\"],\"sender_persons\":[\"Swiss Federal Council\"],\"receiver_persons\":[\"United Nations\"]}}", "model": "mistral-medium-2508", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 68, "total_tokens": 653, "input_cost_usd": 0.00023400000000000002, "output_cost_usd": 0.000136, "estimated_cost_usd": 0.00037}, "duration": 0.784611701965332, "timestamp": "2026-01-24T11:41:51.714073", "parsed": {"metadata": {"letter_title": ["Letter from the Swiss Federal Council to the United Nations"], "send_date": ["1920-07-24"], "sender_persons": ["Swiss Federal Council"], "receiver_persons": ["United Nations"], "document_number": "letter49"}}, "conversation_id": "1a73f15d-de6e-4f79-bc64-7919f62f932a", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"cef0ed4180bd4922b6d44222a2a64cb9\",\"object\":\"chat.completion\",\"model\":\"mistral-medium-2508\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":68,\"total_tokens\":653,\"num_cached_tokens\":576},\"created\":1769251311,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [\\\"Letter from the Swiss Federal Council to the United Nations\\\"],\\n \\\"send_date\\\": [\\\"1920-07-24\\\"],\\n \\\"sender_persons\\\": [\\\"Swiss Federal Council\\\"],\\n \\\"receiver_persons\\\": [\\\"United Nations\\\"]\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 14625, "total_output_tokens": 1537, "total_tokens": 16162, "input_cost_usd": 0.0058499999999999976, "output_cost_usd": 0.003074, "total_cost_usd": 0.008924}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718b22"}, "test_id": "T0523", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-haiku-4-5-20251001", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-04-04\"],\"letter_title\":null,\"sender_persons\":[\"Basler Personenschifffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschifffahrt-Aktiengesellschaft\"]}}", "model": "claude-haiku-4-5-20251001", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 4341, "output_tokens": 106, "total_tokens": 4447, "input_cost_usd": 0.004341, "output_cost_usd": 0.00053, "estimated_cost_usd": 0.004871}, "duration": 2.2732913494110107, "timestamp": "2026-01-24T17:46:57.563444", "parsed": {"metadata": {"letter_title": null, "send_date": ["1928-04-04"], "sender_persons": ["Basler Personenschifffahrtsgesellschaft"], "receiver_persons": ["Basler Rheinschifffahrt-Aktiengesellschaft"], "document_number": "letter24"}}, "conversation_id": "2b49cdc5-83d8-4e59-8a33-d5c4cee9d618", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"msg_01AqYSWtesFTRzWjtVz4VtVj\",\"content\":[{\"id\":\"toolu_015UBw8XHfHNnFEUn73RL5By\",\"input\":{\"metadata\":{\"letter_title\":null,\"send_date\":[\"1928-04-04\"],\"sender_persons\":[\"Basler Personenschifffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschifffahrt-Aktiengesellschaft\"],\"document_number\":\"letter24\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\"}],\"model\":\"claude-haiku-4-5-20251001\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"input_tokens\":4341,\"output_tokens\":106,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.43, "f1_micro": 0.48, "cost_summary": {"total_input_tokens": 85215, "total_output_tokens": 2624, "total_tokens": 87839, "input_cost_usd": 0.08521499999999997, "output_cost_usd": 0.013119999999999998, "total_cost_usd": 0.09833500000000002}}, "normalized_score": 43.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b23"}, "test_id": "T0077", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4o-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-03-24\"],\"letter_title\":[\"Verkauf\"],\"sender_persons\":[\"b.w.\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.-G.\"]}}", "model": "gpt-4o-mini-2024-07-18", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 74159, "output_tokens": 61, "total_tokens": 74220, "input_cost_usd": 0.01112385, "output_cost_usd": 3.6599999999999995e-05, "estimated_cost_usd": 0.011160449999999999}, "duration": 5.299278259277344, "timestamp": "2026-01-24T12:56:35.760253", "parsed": {"metadata": {"send_date": ["1928-03-24"], "letter_title": ["Verkauf"], "sender_persons": ["b.w."], "receiver_persons": ["Basler Rheinschiffahrt A.-G."], "document_number": "letter20"}}, "conversation_id": "fe36624f-67b6-45ba-b815-c1d310879cf2", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D1WXgHnqxuDixqCvxbhtzEh5M4GOa\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1928-03-24\\\"],\\n \\\"letter_title\\\": [\\\"Verkauf\\\"],\\n \\\"sender_persons\\\": [\\\"b.w.\\\"],\\n \\\"receiver_persons\\\": [\\\"Basler Rheinschiffahrt A.-G.\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-03-24\"],\"letter_title\":[\"Verkauf\"],\"sender_persons\":[\"b.w.\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.-G.\"]}}}}],\"created\":1769255792,\"model\":\"gpt-4o-mini-2024-07-18\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":\"fp_8bbc38b4db\",\"usage\":{\"completion_tokens\":61,\"prompt_tokens\":74159,\"total_tokens\":74220,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.48, "f1_micro": 0.54, "cost_summary": {"total_input_tokens": 1301450, "total_output_tokens": 1711, "total_tokens": 1303161, "input_cost_usd": 0.19521750000000004, "output_cost_usd": 0.0010266000000000001, "total_cost_usd": 0.19624410000000003}}, "normalized_score": 48.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b26"}, "test_id": "T0256", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "qwen/qwen3-vl-30b-a3b-instruct", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-06-19\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"Dr. Adolf Bieder\",\"Dr. Hans Burckhardt\",\"Dr. Rudolf Leupold\"],\"receiver_persons\":[\"An die Basler Personenschiffahrtsgeellschaft\"]}}", "model": "qwen/qwen3-vl-30b-a3b-instruct", "provider": "openrouter", "finish_reason": "stop", "usage": {"input_tokens": 3208, "output_tokens": 85, "total_tokens": 3293, "input_cost_usd": 0.0004812, "output_cost_usd": 5.1e-05, "estimated_cost_usd": 0.0005322}, "duration": 3.582754373550415, "timestamp": "2026-01-24T23:10:11.525148", "parsed": {"metadata": {"send_date": ["1928-06-19"], "letter_title": ["null"], "sender_persons": ["Dr. Adolf Bieder", "Dr. Hans Burckhardt", "Dr. Rudolf Leupold"], "receiver_persons": ["An die Basler Personenschiffahrtsgeellschaft"], "document_number": "letter43"}}, "conversation_id": "c5515234-d036-403e-9e3f-54c9d0581c9e", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 1, "sender_persons_fp": 2, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"gen-1769292608-Wgxb5j4NZUE4xZlXGb6W\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1928-06-19\\\"],\\n \\\"letter_title\\\": [\\\"null\\\"],\\n \\\"sender_persons\\\": [\\\"Dr. Adolf Bieder\\\", \\\"Dr. Hans Burckhardt\\\", \\\"Dr. Rudolf Leupold\\\"],\\n \\\"receiver_persons\\\": [\\\"An die Basler Personenschiffahrtsgeellschaft\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-06-19\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"Dr. Adolf Bieder\",\"Dr. Hans Burckhardt\",\"Dr. Rudolf Leupold\"],\"receiver_persons\":[\"An die Basler Personenschiffahrtsgeellschaft\"]}},\"reasoning\":null},\"native_finish_reason\":\"stop\"}],\"created\":1769292608,\"model\":\"qwen/qwen3-vl-30b-a3b-instruct\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":85,\"prompt_tokens\":3208,\"total_tokens\":3293,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":null,\"image_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0,\"video_tokens\":0},\"cost\":0.0007011,\"is_byok\":false,\"cost_details\":{\"upstream_inference_cost\":null,\"upstream_inference_prompt_cost\":0.0006416,\"upstream_inference_completions_cost\":0.0000595}},\"provider\":\"Phala\"}"}, "scoring": {"f1_macro": 0.52, "f1_micro": 0.48, "cost_summary": {"total_input_tokens": 187102, "total_output_tokens": 2594, "total_tokens": 189696, "input_cost_usd": 0.02806530000000002, "output_cost_usd": 0.0015563999999999999, "total_cost_usd": 0.0296217}}, "normalized_score": 52.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b31"}, "test_id": "T0511", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-opus-4-5-20251101", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-02-16\"],\"letter_title\":null,\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Christ\"]}}", "model": "claude-opus-4-5-20251101", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 5895, "output_tokens": 84, "total_tokens": 5979, "input_cost_usd": 0.029475, "output_cost_usd": 0.0021, "estimated_cost_usd": 0.031575}, "duration": 5.349233150482178, "timestamp": "2026-01-24T16:30:10.720628", "parsed": {"metadata": {"send_date": ["1926-02-16"], "letter_title": null, "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Christ"], "document_number": "letter01"}}, "conversation_id": "c494ad5b-4d8c-4708-a00a-537c38bb3f8e", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"msg_015tgQ2dNFW84qtHmLM8L1Qq\",\"content\":[{\"id\":\"toolu_0183UjJQ12LLD1xgJGL3R1m2\",\"input\":{\"metadata\":{\"send_date\":[\"1926-02-16\"],\"letter_title\":null,\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Christ\"],\"document_number\":\"letter01\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\"}],\"model\":\"claude-opus-4-5-20251101\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"input_tokens\":5895,\"output_tokens\":84,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.58, "f1_micro": 0.59, "cost_summary": {"total_input_tokens": 222573, "total_output_tokens": 5132, "total_tokens": 227705, "input_cost_usd": 1.1128650000000004, "output_cost_usd": 0.1283, "total_cost_usd": 1.241165}}, "normalized_score": 57.99999999999999}, {"_id": {"$oid": "69d4eb12b877594bc5718b32"}, "test_id": "T0125", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-pro", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-03-24\"],\"letter_title\":[\"Ankauf des Schiffes 'Rheinfelden'\"],\"sender_persons\":[\"Basler Personenschiffahrtgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.-G.\"]}}", "model": "gemini-2.5-pro", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 852, "output_tokens": 108, "total_tokens": 2076, "input_cost_usd": 0.001065, "output_cost_usd": 0.00108, "estimated_cost_usd": 0.002145}, "duration": 10.975351095199585, "timestamp": "2026-01-24T11:24:21.887043", "parsed": {"metadata": {"send_date": ["1928-03-24"], "letter_title": ["Ankauf des Schiffes 'Rheinfelden'"], "sender_persons": ["Basler Personenschiffahrtgesellschaft"], "receiver_persons": ["Basler Rheinschiffahrt A.-G."], "document_number": "letter20"}}, "conversation_id": "0c456f50-b2ae-468d-bd5e-74fa4e5d0537", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Sat, 24 Jan 2026 10:24:21 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=10696\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"video_metadata\":null,\"thought\":null,\"inline_data\":null,\"file_data\":null,\"thought_signature\":null,\"function_call\":null,\"code_execution_result\":null,\"executable_code\":null,\"function_response\":null,\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1928-03-24\\\"\\n ],\\n \\\"letter_title\\\": [\\n \\\"Ankauf des Schiffes 'Rheinfelden'\\\"\\n ],\\n \\\"sender_persons\\\": [\\n \\\"Basler Personenschiffahrtgesellschaft\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Basler Rheinschiffahrt A.-G.\\\"\\n ]\\n }\\n}\"}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"url_context_metadata\":null,\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null}],\"create_time\":null,\"model_version\":\"gemini-2.5-pro\",\"prompt_feedback\":null,\"response_id\":\"1Z10abeDMu_NnsEPkL2gkAw\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":108,\"candidates_tokens_details\":null,\"prompt_token_count\":852,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":336},{\"modality\":\"IMAGE\",\"token_count\":516}],\"thoughts_token_count\":1116,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":2076,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1928-03-24\"],\"letter_title\":[\"Ankauf des Schiffes 'Rheinfelden'\"],\"sender_persons\":[\"Basler Personenschiffahrtgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.-G.\"]}}}"}, "scoring": {"f1_macro": 0.55, "f1_micro": 0.65, "cost_summary": {"total_input_tokens": 17430, "total_output_tokens": 2272, "total_tokens": 19702, "input_cost_usd": 0.0217875, "output_cost_usd": 0.02272, "total_cost_usd": 0.044507500000000005}}, "normalized_score": 55.00000000000001}, {"_id": {"$oid": "69d4eb12b877594bc5718b34"}, "test_id": "T0102", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-opus-4-20250514", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\": {\"send_date\": [\"1928-02-18\"], \"letter_title\": [null], \"sender_persons\": [\"Basler Rheinschiffahrt-Aktiengesellschaft\"], \"receiver_persons\": [\"Vorstand der Basler Personenschiffahrts-Gesellschaft\"]}}", "model": "claude-opus-4-20250514", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 10284, "output_tokens": 115, "total_tokens": 10399, "input_cost_usd": 0.15426, "output_cost_usd": 0.008625, "estimated_cost_usd": 0.162885}, "duration": 5.992280006408691, "timestamp": "2026-01-24T11:21:18.269264", "parsed": {"metadata": {"send_date": ["1928-02-18"], "letter_title": [null], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Vorstand der Basler Personenschiffahrts-Gesellschaft"], "document_number": "letter14"}}, "conversation_id": "9f614b4b-9d92-4087-b9b0-7834070d33aa", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"msg_01Gx5kQCAP2xx2GcV5qnu5y2\",\"content\":[{\"id\":\"toolu_01PhhAWS6PRWYgmL5zZbncmt\",\"input\":{\"metadata\":{\"send_date\":[\"1928-02-18\"],\"letter_title\":[null],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Vorstand der Basler Personenschiffahrts-Gesellschaft\"],\"document_number\":\"letter14\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\"}],\"model\":\"claude-opus-4-20250514\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"input_tokens\":10284,\"output_tokens\":115,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.46, "f1_micro": 0.42, "cost_summary": {"total_input_tokens": 128622, "total_output_tokens": 3573, "total_tokens": 132195, "input_cost_usd": 1.9293299999999993, "output_cost_usd": 0.26797499999999996, "total_cost_usd": 2.197305}}, "normalized_score": 46.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b35"}, "test_id": "T0175", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-medium-2508", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1940-06-25\"],\"letter_title\":[\"Letter from the Swiss Federal Council\"],\"sender_persons\":[\"Swiss Federal Council\"],\"receiver_persons\":[\"Reich Minister of Public Enlightenment and Propaganda\"]}}", "model": "mistral-medium-2508", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 70, "total_tokens": 655, "input_cost_usd": 0.00023400000000000002, "output_cost_usd": 0.00014, "estimated_cost_usd": 0.000374}, "duration": 1.0280120372772217, "timestamp": "2026-01-24T11:42:34.771448", "parsed": {"metadata": {"letter_title": ["Letter from the Swiss Federal Council"], "send_date": ["1940-06-25"], "sender_persons": ["Swiss Federal Council"], "receiver_persons": ["Reich Minister of Public Enlightenment and Propaganda"], "document_number": "letter29"}}, "conversation_id": "91a95cf1-3dd7-4f5a-bf21-d1c6131a84f5", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"a4b973aaa3484a839a8a831ec1316399\",\"object\":\"chat.completion\",\"model\":\"mistral-medium-2508\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":70,\"total_tokens\":655,\"num_cached_tokens\":576},\"created\":1769251353,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [\\\"Letter from the Swiss Federal Council\\\"],\\n \\\"send_date\\\": [\\\"1940-06-25\\\"],\\n \\\"sender_persons\\\": [\\\"Swiss Federal Council\\\"],\\n \\\"receiver_persons\\\": [\\\"Reich Minister of Public Enlightenment and Propaganda\\\"]\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 18720, "total_output_tokens": 2057, "total_tokens": 20777, "input_cost_usd": 0.007487999999999996, "output_cost_usd": 0.0041140000000000005, "total_cost_usd": 0.011602}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718b36"}, "test_id": "T0512", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-opus-4-5-20251101", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1935-08-17\"],\"letter_title\":null,\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Fritz Ritter\"]}}", "model": "claude-opus-4-5-20251101", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 2787, "output_tokens": 83, "total_tokens": 2870, "input_cost_usd": 0.013935, "output_cost_usd": 0.002075, "estimated_cost_usd": 0.01601}, "duration": 5.0463926792144775, "timestamp": "2026-01-24T16:36:27.925933", "parsed": {"metadata": {"send_date": ["1935-08-17"], "letter_title": null, "sender_persons": ["Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["Fritz Ritter"], "document_number": "letter65"}}, "conversation_id": "6b1e0884-9eab-4dea-bc7f-9fb7d9b5baa8", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"msg_011rnCYZYK7gqBDB2mkFut88\",\"content\":[{\"id\":\"toolu_01RVmVSArApDqJpkJRSFAhE4\",\"input\":{\"metadata\":{\"send_date\":[\"1935-08-17\"],\"letter_title\":null,\"sender_persons\":[\"Basler Personenschiffahrtsgesellschaft\"],\"receiver_persons\":[\"Fritz Ritter\"],\"document_number\":\"letter65\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\"}],\"model\":\"claude-opus-4-5-20251101\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"input_tokens\":2787,\"output_tokens\":83,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.53, "f1_micro": 0.62, "cost_summary": {"total_input_tokens": 85215, "total_output_tokens": 2204, "total_tokens": 87419, "input_cost_usd": 0.42607499999999976, "output_cost_usd": 0.055099999999999996, "total_cost_usd": 0.4811750000000001}}, "normalized_score": 53.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b39"}, "test_id": "T0012", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4o-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-10-04\"],\"letter_title\":[\"Letter to Dr. Max Vischer\"],\"sender_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft\"],\"receiver_persons\":[\"Dr. Max Vischer\"]}}", "model": "gpt-4o-mini-2024-07-18", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 110994, "output_tokens": 66, "total_tokens": 111060, "input_cost_usd": 0.0166491, "output_cost_usd": 3.96e-05, "estimated_cost_usd": 0.0166887}, "duration": 6.669918775558472, "timestamp": "2026-01-24T11:15:04.215032", "parsed": {"metadata": {"send_date": ["1932-10-04"], "letter_title": ["Letter to Dr. Max Vischer"], "sender_persons": ["Basler Rheinschiffahrt Aktiengesellschaft"], "receiver_persons": ["Dr. Max Vischer"], "document_number": "letter52"}}, "conversation_id": "decc6061-8bb2-4226-9b4e-f6af467cfe63", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D1UxRGHRFqt6y2JtD5Nxig3UNV5VZ\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1932-10-04\\\"],\\n \\\"letter_title\\\": [\\\"Letter to Dr. Max Vischer\\\"],\\n \\\"sender_persons\\\": [\\\"Basler Rheinschiffahrt Aktiengesellschaft\\\"],\\n \\\"receiver_persons\\\": [\\\"Dr. Max Vischer\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1932-10-04\"],\"letter_title\":[\"Letter to Dr. Max Vischer\"],\"sender_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft\"],\"receiver_persons\":[\"Dr. Max Vischer\"]}}}}],\"created\":1769249701,\"model\":\"gpt-4o-mini-2024-07-18\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":\"fp_8bbc38b4db\",\"usage\":{\"completion_tokens\":66,\"prompt_tokens\":110994,\"total_tokens\":111060,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.5, "f1_micro": 0.5, "cost_summary": {"total_input_tokens": 3637703, "total_output_tokens": 3938, "total_tokens": 3641641, "input_cost_usd": 0.5456554500000002, "output_cost_usd": 0.0023628, "total_cost_usd": 0.54801825}}, "normalized_score": 50.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b41"}, "test_id": "T0117", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-opus-4-1-20250805", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-08-13\"],\"letter_title\":null,\"sender_persons\":[\"J.A.Ritter\"],\"receiver_persons\":[\"Dr. Max Vischer\"]}}", "model": "claude-opus-4-1-20250805", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 5622, "output_tokens": 92, "total_tokens": 5714, "input_cost_usd": 0.08433, "output_cost_usd": 0.0069, "estimated_cost_usd": 0.09123}, "duration": 4.956783771514893, "timestamp": "2026-01-24T11:36:54.050152", "parsed": {"metadata": {"letter_title": null, "send_date": ["1926-08-13"], "sender_persons": ["J.A.Ritter"], "receiver_persons": ["Dr. Max Vischer"], "document_number": "letter12"}}, "conversation_id": "7ebac447-a1e4-4df6-b2ba-c193acc99b83", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 1, "sender_persons_fp": 0, "sender_persons_fn": 1, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"msg_019CRoBiQYok8J7k3y2AQh2g\",\"content\":[{\"id\":\"toolu_01WPFJLkqu1h65yM7TtqXvki\",\"input\":{\"metadata\":{\"letter_title\":null,\"send_date\":[\"1926-08-13\"],\"sender_persons\":[\"J.A.Ritter\"],\"receiver_persons\":[\"Dr. Max Vischer\"],\"document_number\":\"letter12\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\"}],\"model\":\"claude-opus-4-1-20250805\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"input_tokens\":5622,\"output_tokens\":92,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.45, "f1_micro": 0.46, "cost_summary": {"total_input_tokens": 207012, "total_output_tokens": 6071, "total_tokens": 213083, "input_cost_usd": 3.105180000000002, "output_cost_usd": 0.4553250000000001, "total_cost_usd": 3.5605049999999996}}, "normalized_score": 45.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b46"}, "test_id": "T0171", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-medium-2508", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1955-04-12\"],\"letter_title\":[\"Letter from Albert Einstein to Swiss Federal Council\"],\"sender_persons\":[\"Albert Einstein\"],\"receiver_persons\":[\"Swiss Federal Council\"]}}", "model": "mistral-medium-2508", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 66, "total_tokens": 651, "input_cost_usd": 0.00023400000000000002, "output_cost_usd": 0.000132, "estimated_cost_usd": 0.000366}, "duration": 0.9478375911712646, "timestamp": "2026-01-24T11:40:08.727993", "parsed": {"metadata": {"letter_title": ["Letter from Albert Einstein to Swiss Federal Council"], "send_date": ["1955-04-12"], "sender_persons": ["Albert Einstein"], "receiver_persons": ["Swiss Federal Council"], "document_number": "letter46"}}, "conversation_id": "c1d82524-6d27-464e-8930-dc419c50d6fc", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"4a581d4c43be42af903cbe66ec90e883\",\"object\":\"chat.completion\",\"model\":\"mistral-medium-2508\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":66,\"total_tokens\":651,\"num_cached_tokens\":576},\"created\":1769251208,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [\\\"Letter from Albert Einstein to Swiss Federal Council\\\"],\\n \\\"send_date\\\": [\\\"1955-04-12\\\"],\\n \\\"sender_persons\\\": [\\\"Albert Einstein\\\"],\\n \\\"receiver_persons\\\": [\\\"Swiss Federal Council\\\"]\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 33345, "total_output_tokens": 3634, "total_tokens": 36979, "input_cost_usd": 0.013337999999999992, "output_cost_usd": 0.007268000000000004, "total_cost_usd": 0.02060599999999999}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718b48"}, "test_id": "T0070", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4.1-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-05-05\"],\"letter_title\":[\"Abschrift\"],\"sender_persons\":[\"Herr Direktor W. Stauffacher\"],\"receiver_persons\":[\"Basler Rheinschifffahrts-A.G.\"]}}", "model": "gpt-4.1-mini-2025-04-14", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 2875, "output_tokens": 53, "total_tokens": 2928, "input_cost_usd": 0.00115, "output_cost_usd": 8.48e-05, "estimated_cost_usd": 0.0012347999999999999}, "duration": 3.165675401687622, "timestamp": "2026-01-24T12:39:48.871562", "parsed": {"metadata": {"send_date": ["1928-05-05"], "letter_title": ["Abschrift"], "sender_persons": ["Herr Direktor W. Stauffacher"], "receiver_persons": ["Basler Rheinschifffahrts-A.G."], "document_number": "letter33"}}, "conversation_id": "0561b8b5-f18d-4689-82d3-a4538ced0d49", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D1WHTbWIwSKX4rNZVIEWrMT1SCjR2\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1928-05-05\\\"],\\\"letter_title\\\":[\\\"Abschrift\\\"],\\\"sender_persons\\\":[\\\"Herr Direktor W. Stauffacher\\\"],\\\"receiver_persons\\\":[\\\"Basler Rheinschifffahrts-A.G.\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-05-05\"],\"letter_title\":[\"Abschrift\"],\"sender_persons\":[\"Herr Direktor W. Stauffacher\"],\"receiver_persons\":[\"Basler Rheinschifffahrts-A.G.\"]}}}}],\"created\":1769254787,\"model\":\"gpt-4.1-mini-2025-04-14\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":\"fp_376a7ccef1\",\"usage\":{\"completion_tokens\":53,\"prompt_tokens\":2875,\"total_tokens\":2928,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.54, "f1_micro": 0.54, "cost_summary": {"total_input_tokens": 261701, "total_output_tokens": 3117, "total_tokens": 264818, "input_cost_usd": 0.10468039999999999, "output_cost_usd": 0.0049872000000000015, "total_cost_usd": 0.10966760000000005}}, "normalized_score": 54.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b49"}, "test_id": "T0104", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-sonnet-4-20250514", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-08-13\"],\"letter_title\":null,\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Dr. Max Vischer\"]}}", "model": "claude-sonnet-4-20250514", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 5622, "output_tokens": 99, "total_tokens": 5721, "input_cost_usd": 0.016866, "output_cost_usd": 0.001485, "estimated_cost_usd": 0.018351}, "duration": 4.5322394371032715, "timestamp": "2026-01-24T11:27:28.373946", "parsed": {"metadata": {"letter_title": null, "send_date": ["1926-08-13"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Dr. Max Vischer"], "document_number": "letter12"}}, "conversation_id": "2c157ec1-decb-42fd-8f62-688923f9a414", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"msg_01B2ta8dgss8NfiNtC7iMpsX\",\"content\":[{\"id\":\"toolu_01Q9xsqQKtx9wL7qePG8Pq9i\",\"input\":{\"metadata\":{\"letter_title\":null,\"send_date\":[\"1926-08-13\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Dr. Max Vischer\"],\"document_number\":\"letter12\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\"}],\"model\":\"claude-sonnet-4-20250514\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"input_tokens\":5622,\"output_tokens\":99,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.32, "f1_micro": 0.39, "cost_summary": {"total_input_tokens": 78390, "total_output_tokens": 2522, "total_tokens": 80912, "input_cost_usd": 0.23516999999999988, "output_cost_usd": 0.03783, "total_cost_usd": 0.273}}, "normalized_score": 32.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b51"}, "test_id": "T0226", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-sonnet-4-5-20250929", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-03-26\"],\"letter_title\":null,\"sender_persons\":[\"K/L\"],\"receiver_persons\":[\"Christ\"]}}", "model": "claude-sonnet-4-5-20250929", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 2787, "output_tokens": 80, "total_tokens": 2867, "input_cost_usd": 0.008361, "output_cost_usd": 0.0012000000000000001, "estimated_cost_usd": 0.009561}, "duration": 2.6639602184295654, "timestamp": "2026-01-24T13:54:52.321140", "parsed": {"metadata": {"letter_title": null, "send_date": ["1926-03-26"], "sender_persons": ["K/L"], "receiver_persons": ["Christ"], "document_number": "letter04"}}, "conversation_id": "e4fb8c5b-81e9-43a2-af73-232778d5efb1", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 1, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"msg_01CymtYicEhw6Wms7sZgDuaB\",\"content\":[{\"id\":\"toolu_01ALJMRdxzx6QtGD35feph32\",\"input\":{\"metadata\":{\"letter_title\":null,\"send_date\":[\"1926-03-26\"],\"sender_persons\":[\"K/L\"],\"receiver_persons\":[\"Christ\"],\"document_number\":\"letter04\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\"}],\"model\":\"claude-sonnet-4-5-20250929\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"input_tokens\":2787,\"output_tokens\":80,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.46, "f1_micro": 0.47, "cost_summary": {"total_input_tokens": 222573, "total_output_tokens": 5758, "total_tokens": 228331, "input_cost_usd": 0.6677189999999996, "output_cost_usd": 0.08636999999999999, "total_cost_usd": 0.7540889999999995}}, "normalized_score": 46.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b59"}, "test_id": "T0073", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4.1-nano", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-03-26\"],\"letter_title\":[\"Mitteilung \u00fcber Verhandlungen der Rheinschiffahrts-Aktiengesellschaft\"],\"sender_persons\":[\"W. W. Marring\"],\"receiver_persons\":[\"Christ c/o. Paravicini\"]}}", "model": "gpt-4.1-nano-2025-04-14", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 4112, "output_tokens": 63, "total_tokens": 4175, "input_cost_usd": 0.0004112, "output_cost_usd": 2.5200000000000003e-05, "estimated_cost_usd": 0.00043640000000000004}, "duration": 2.0704219341278076, "timestamp": "2026-01-24T12:45:09.527251", "parsed": {"metadata": {"send_date": ["1926-03-26"], "letter_title": ["Mitteilung \u00fcber Verhandlungen der Rheinschiffahrts-Aktiengesellschaft"], "sender_persons": ["W. W. Marring"], "receiver_persons": ["Christ c/o. Paravicini"], "document_number": "letter04"}}, "conversation_id": "f44d6230-1935-4452-9578-e0f93de9023d", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"chatcmpl-D1WMeRimLuriBkN61vrVajWMioJgX\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1926-03-26\\\"],\\\"letter_title\\\": [\\\"Mitteilung \u00fcber Verhandlungen der Rheinschiffahrts-Aktiengesellschaft\\\"],\\\"sender_persons\\\": [\\\"W. W. Marring\\\"],\\\"receiver_persons\\\": [\\\"Christ c/o. Paravicini\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1926-03-26\"],\"letter_title\":[\"Mitteilung \u00fcber Verhandlungen der Rheinschiffahrts-Aktiengesellschaft\"],\"sender_persons\":[\"W. W. Marring\"],\"receiver_persons\":[\"Christ c/o. Paravicini\"]}}}}],\"created\":1769255108,\"model\":\"gpt-4.1-nano-2025-04-14\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":\"fp_2b9b3207a6\",\"usage\":{\"completion_tokens\":63,\"prompt_tokens\":4112,\"total_tokens\":4175,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.46, "f1_micro": 0.47, "cost_summary": {"total_input_tokens": 382927, "total_output_tokens": 3170, "total_tokens": 386097, "input_cost_usd": 0.03829270000000002, "output_cost_usd": 0.001268, "total_cost_usd": 0.039560700000000004}}, "normalized_score": 46.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b5c"}, "test_id": "T0214", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-flash-lite-preview-09-2025", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-09-07\"],\"letter_title\":[\"Betr. Personenschiffahrt\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Dr. M. Vischer-von Planta\"]}}", "model": "gemini-2.5-flash-lite-preview-09-2025", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 1110, "output_tokens": 108, "total_tokens": 1218, "input_cost_usd": 0.00011100000000000001, "output_cost_usd": 4.32e-05, "estimated_cost_usd": 0.0001542}, "duration": 1.2088837623596191, "timestamp": "2026-01-24T13:52:53.385610", "parsed": {"metadata": {"send_date": ["1932-09-07"], "letter_title": ["Betr. Personenschiffahrt"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Dr. M. Vischer-von Planta"], "document_number": "letter48"}}, "conversation_id": "b189c35a-18c4-49d6-8e26-4598f3adb2df", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Sat, 24 Jan 2026 12:52:53 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=783\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"video_metadata\":null,\"thought\":null,\"inline_data\":null,\"file_data\":null,\"thought_signature\":null,\"function_call\":null,\"code_execution_result\":null,\"executable_code\":null,\"function_response\":null,\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1932-09-07\\\"\\n ],\\n \\\"letter_title\\\": [\\n \\\"Betr. Personenschiffahrt\\\"\\n ],\\n \\\"sender_persons\\\": [\\n \\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Dr. M. Vischer-von Planta\\\"\\n ]\\n }\\n}\"}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"url_context_metadata\":null,\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null}],\"create_time\":null,\"model_version\":\"gemini-2.5-flash-lite-preview-09-2025\",\"prompt_feedback\":null,\"response_id\":\"pcB0aeSIFeeD7M8P4-mY0Qo\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":108,\"candidates_tokens_details\":null,\"prompt_token_count\":1110,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":336},{\"modality\":\"IMAGE\",\"token_count\":774}],\"thoughts_token_count\":null,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":1218,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1932-09-07\"],\"letter_title\":[\"Betr. Personenschiffahrt\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Dr. M. Vischer-von Planta\"]}}}"}, "scoring": {"f1_macro": 0.51, "f1_micro": 0.46, "cost_summary": {"total_input_tokens": 27006, "total_output_tokens": 3596, "total_tokens": 30602, "input_cost_usd": 0.0027006000000000005, "output_cost_usd": 0.0014384, "total_cost_usd": 0.004139000000000002}}, "normalized_score": 51.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b64"}, "test_id": "T0072", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4.1-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-09-07\"],\"letter_title\":[\"Betr. Personenschiffahrt\"],\"sender_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft\"],\"receiver_persons\":[\"Dr. M. Vischer-von Planta\"]}}", "model": "gpt-4.1-mini-2025-04-14", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 7647, "output_tokens": 56, "total_tokens": 7703, "cached_tokens": 4864, "input_cost_usd": 0.0030588000000000004, "output_cost_usd": 8.960000000000001e-05, "estimated_cost_usd": 0.0031484000000000004}, "duration": 4.110058069229126, "timestamp": "2026-01-24T12:44:06.135901", "parsed": {"metadata": {"send_date": ["1932-09-07"], "letter_title": ["Betr. Personenschiffahrt"], "sender_persons": ["Basler Rheinschiffahrt Aktiengesellschaft"], "receiver_persons": ["Dr. M. Vischer-von Planta"], "document_number": "letter48"}}, "conversation_id": "8278d7c4-84e9-4750-bd81-21952dc1e216", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D1WLdgvKz5WMzXSG9XuVfF2KnHCfY\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1932-09-07\\\"],\\\"letter_title\\\":[\\\"Betr. Personenschiffahrt\\\"],\\\"sender_persons\\\":[\\\"Basler Rheinschiffahrt Aktiengesellschaft\\\"],\\\"receiver_persons\\\":[\\\"Dr. M. Vischer-von Planta\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1932-09-07\"],\"letter_title\":[\"Betr. Personenschiffahrt\"],\"sender_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft\"],\"receiver_persons\":[\"Dr. M. Vischer-von Planta\"]}}}}],\"created\":1769255045,\"model\":\"gpt-4.1-mini-2025-04-14\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":\"fp_376a7ccef1\",\"usage\":{\"completion_tokens\":56,\"prompt_tokens\":7647,\"total_tokens\":7703,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":4864}}}"}, "scoring": {"f1_macro": 0.6, "f1_micro": 0.53, "cost_summary": {"total_input_tokens": 165966, "total_output_tokens": 1831, "total_tokens": 167797, "input_cost_usd": 0.06638639999999998, "output_cost_usd": 0.0029295999999999992, "total_cost_usd": 0.06931599999999999}}, "normalized_score": 60.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b66"}, "test_id": "T0427", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "magistral-medium-2509", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":null,\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":null}}", "model": "magistral-medium-2509", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 32, "total_tokens": 617, "input_cost_usd": 0.00117, "output_cost_usd": 0.00015999999999999999, "estimated_cost_usd": 0.00133}, "duration": 0.5539803504943848, "timestamp": "2026-01-24T12:39:39.365578", "parsed": {"metadata": {"send_date": null, "letter_title": null, "sender_persons": null, "receiver_persons": null, "document_number": "letter61"}}, "conversation_id": "4bfbba0e-b191-4d84-a02e-639984850d59", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"e0fb2c585c50482d9d79a39082d99aac\",\"object\":\"chat.completion\",\"model\":\"magistral-medium-2509\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":32,\"total_tokens\":617,\"num_cached_tokens\":704},\"created\":1769254779,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\\"metadata\\\": {\\\"send_date\\\": null, \\\"letter_title\\\": null, \\\"sender_persons\\\": null, \\\"receiver_persons\\\": null}}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 14625, "total_output_tokens": 1020, "total_tokens": 15645, "input_cost_usd": 0.029250000000000016, "output_cost_usd": 0.005099999999999999, "total_cost_usd": 0.03435}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718b6d"}, "test_id": "T0057", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.0-flash-lite", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-09-28\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"Dr. Max Vischer\"]}}", "model": "gemini-2.0-flash-lite", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 2203, "output_tokens": 89, "total_tokens": 2292, "input_cost_usd": 0.000165225, "output_cost_usd": 2.67e-05, "estimated_cost_usd": 0.000191925}, "duration": 1.9428203105926514, "timestamp": "2026-01-24T11:12:24.860015", "parsed": {"metadata": {"send_date": ["1928-09-28"], "letter_title": ["null"], "sender_persons": ["null"], "receiver_persons": ["Dr. Max Vischer"], "document_number": "letter45"}}, "conversation_id": "90155e37-d706-4ab8-8557-98647d14fdf8", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 1, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Sat, 24 Jan 2026 10:12:24 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=1689\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"video_metadata\":null,\"thought\":null,\"inline_data\":null,\"file_data\":null,\"thought_signature\":null,\"function_call\":null,\"code_execution_result\":null,\"executable_code\":null,\"function_response\":null,\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1928-09-28\\\"\\n ],\\n \\\"letter_title\\\": [\\n \\\"null\\\"\\n ],\\n \\\"sender_persons\\\": [\\n \\\"null\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Dr. Max Vischer\\\"\\n ]\\n }\\n}\"}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"url_context_metadata\":null,\"avg_logprobs\":-0.0057412894924035235,\"grounding_metadata\":null,\"index\":null,\"logprobs_result\":null,\"safety_ratings\":null}],\"create_time\":null,\"model_version\":\"gemini-2.0-flash-lite\",\"prompt_feedback\":null,\"response_id\":\"B5t0acf9B5ennsEP0aGz-A0\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":89,\"candidates_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":89}],\"prompt_token_count\":2203,\"prompt_tokens_details\":[{\"modality\":\"IMAGE\",\"token_count\":1806},{\"modality\":\"TEXT\",\"token_count\":397}],\"thoughts_token_count\":null,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":2292,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1928-09-28\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"Dr. Max Vischer\"]}}}"}, "scoring": {"f1_macro": 0.55, "f1_micro": 0.51, "cost_summary": {"total_input_tokens": 52178, "total_output_tokens": 3135, "total_tokens": 55313, "input_cost_usd": 0.003913350000000002, "output_cost_usd": 0.0009404999999999999, "total_cost_usd": 0.00485385}}, "normalized_score": 55.00000000000001}, {"_id": {"$oid": "69d4eb12b877594bc5718b6e"}, "test_id": "T0013", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.0-flash", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1926-03-04\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Herrn P. Christ\"]}}", "model": "gemini-2.0-flash", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 1687, "output_tokens": 74, "total_tokens": 1761, "input_cost_usd": 0.0001687, "output_cost_usd": 2.96e-05, "estimated_cost_usd": 0.0001983}, "duration": 2.388331174850464, "timestamp": "2026-01-24T11:03:43.329204", "parsed": {"metadata": {"send_date": ["1926-03-04"], "letter_title": ["null"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Herrn P. Christ"], "document_number": "letter02"}}, "conversation_id": "037927dc-be81-4cd2-9804-70f6280bd943", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 1, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Sat, 24 Jan 2026 10:03:43 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=1628\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"video_metadata\":null,\"thought\":null,\"inline_data\":null,\"file_data\":null,\"thought_signature\":null,\"function_call\":null,\"code_execution_result\":null,\"executable_code\":null,\"function_response\":null,\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1926-03-04\\\"],\\n \\\"letter_title\\\": [\\\"null\\\"],\\n \\\"sender_persons\\\": [\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"],\\n \\\"receiver_persons\\\": [\\\"Herrn P. Christ\\\"]\\n }\\n}\"}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"url_context_metadata\":null,\"avg_logprobs\":-0.02319674556319778,\"grounding_metadata\":null,\"index\":null,\"logprobs_result\":null,\"safety_ratings\":null}],\"create_time\":null,\"model_version\":\"gemini-2.0-flash\",\"prompt_feedback\":null,\"response_id\":\"_Zh0aaKuMIO8nsEPm-a4oAw\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":74,\"candidates_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":74}],\"prompt_token_count\":1687,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":397},{\"modality\":\"IMAGE\",\"token_count\":1290}],\"thoughts_token_count\":null,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":1761,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1926-03-04\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Herrn P. Christ\"]}}}"}, "scoring": {"f1_macro": 0.51, "f1_micro": 0.5, "cost_summary": {"total_input_tokens": 98997, "total_output_tokens": 5013, "total_tokens": 104010, "input_cost_usd": 0.009899699999999994, "output_cost_usd": 0.0020052000000000004, "total_cost_usd": 0.011904900000000005}}, "normalized_score": 51.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b71"}, "test_id": "T0176", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-medium-2505", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1940-06-28\"],\"letter_title\":[\"Letter from the Swiss Federal Council\"],\"sender_persons\":[\"Swiss Federal Council\"],\"receiver_persons\":[\"Reich Minister of Public Enlightenment and Propaganda\"]}}", "model": "mistral-medium-2505", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 70, "total_tokens": 655, "input_cost_usd": 0.00023400000000000002, "output_cost_usd": 0.00014, "estimated_cost_usd": 0.000374}, "duration": 0.8438272476196289, "timestamp": "2026-01-24T11:43:24.311430", "parsed": {"metadata": {"letter_title": ["Letter from the Swiss Federal Council"], "send_date": ["1940-06-28"], "sender_persons": ["Swiss Federal Council"], "receiver_persons": ["Reich Minister of Public Enlightenment and Propaganda"], "document_number": "letter64"}}, "conversation_id": "a4547dd3-1ff8-4a4e-b238-2c4599e835a2", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"d0f55085b2a14959842c988e0298b9b4\",\"object\":\"chat.completion\",\"model\":\"mistral-medium-2505\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":70,\"total_tokens\":655,\"num_cached_tokens\":576},\"created\":1769251403,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [\\\"Letter from the Swiss Federal Council\\\"],\\n \\\"send_date\\\": [\\\"1940-06-28\\\"],\\n \\\"sender_persons\\\": [\\\"Swiss Federal Council\\\"],\\n \\\"receiver_persons\\\": [\\\"Reich Minister of Public Enlightenment and Propaganda\\\"]\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 18720, "total_output_tokens": 2099, "total_tokens": 20819, "input_cost_usd": 0.007487999999999996, "output_cost_usd": 0.004198000000000001, "total_cost_usd": 0.011686}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718b72"}, "test_id": "T0043", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4o-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-10-07\"],\"letter_title\":[\"Basler Personenschifffahrtsgesellschaft\"],\"sender_persons\":[\"Basler Personenschifffahrtsgesellschaft\"],\"receiver_persons\":[\"Vorstandsmitglieder der Basler Personenschifffahrtsgesellschaft\"]}}", "model": "gpt-4o-mini-2024-07-18", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 37324, "output_tokens": 77, "total_tokens": 37401, "cached_tokens": 1280, "input_cost_usd": 0.0055986000000000005, "output_cost_usd": 4.62e-05, "estimated_cost_usd": 0.0056448}, "duration": 3.646939277648926, "timestamp": "2026-01-24T11:27:24.880527", "parsed": {"metadata": {"send_date": ["1932-10-07"], "letter_title": ["Basler Personenschifffahrtsgesellschaft"], "sender_persons": ["Basler Personenschifffahrtsgesellschaft"], "receiver_persons": ["Vorstandsmitglieder der Basler Personenschifffahrtsgesellschaft"], "document_number": "letter53"}}, "conversation_id": "a096bb73-1cab-4ef3-9ad8-7da564a55869", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-D1V9OqlSnnNKYXkvJUUYPAzqVPZ8X\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1932-10-07\\\"],\\n \\\"letter_title\\\": [\\\"Basler Personenschifffahrtsgesellschaft\\\"],\\n \\\"sender_persons\\\": [\\\"Basler Personenschifffahrtsgesellschaft\\\"],\\n \\\"receiver_persons\\\": [\\\"Vorstandsmitglieder der Basler Personenschifffahrtsgesellschaft\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1932-10-07\"],\"letter_title\":[\"Basler Personenschifffahrtsgesellschaft\"],\"sender_persons\":[\"Basler Personenschifffahrtsgesellschaft\"],\"receiver_persons\":[\"Vorstandsmitglieder der Basler Personenschifffahrtsgesellschaft\"]}}}}],\"created\":1769250442,\"model\":\"gpt-4o-mini-2024-07-18\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":\"fp_8bbc38b4db\",\"usage\":{\"completion_tokens\":77,\"prompt_tokens\":37324,\"total_tokens\":37401,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":1280}}}"}, "scoring": {"f1_macro": 0.53, "f1_micro": 0.49, "cost_summary": {"total_input_tokens": 2336253, "total_output_tokens": 2259, "total_tokens": 2338512, "input_cost_usd": 0.3504379500000001, "output_cost_usd": 0.0013553999999999997, "total_cost_usd": 0.35179334999999995}}, "normalized_score": 53.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b74"}, "test_id": "T0124", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-pro", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1932-10-10\"],\"letter_title\":null,\"sender_persons\":[\"Jean Frey\"],\"receiver_persons\":[\"Dr. Max Vischer\"]}}", "model": "gemini-2.5-pro", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 594, "output_tokens": 83, "total_tokens": 1321, "input_cost_usd": 0.0007425, "output_cost_usd": 0.00083, "estimated_cost_usd": 0.0015725000000000001}, "duration": 7.215069532394409, "timestamp": "2026-01-24T11:21:51.991067", "parsed": {"metadata": {"send_date": ["1932-10-10"], "letter_title": null, "sender_persons": ["Jean Frey"], "receiver_persons": ["Dr. Max Vischer"], "document_number": "letter55"}}, "conversation_id": "53285f35-802b-4ed7-8389-988dfe3a429d", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 1, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Sat, 24 Jan 2026 10:21:51 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=7061\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"video_metadata\":null,\"thought\":null,\"inline_data\":null,\"file_data\":null,\"thought_signature\":null,\"function_call\":null,\"code_execution_result\":null,\"executable_code\":null,\"function_response\":null,\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1932-10-10\\\"\\n ],\\n \\\"letter_title\\\": null,\\n \\\"sender_persons\\\": [\\n \\\"Jean Frey\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Dr. Max Vischer\\\"\\n ]\\n }\\n}\"}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"url_context_metadata\":null,\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null}],\"create_time\":null,\"model_version\":\"gemini-2.5-pro\",\"prompt_feedback\":null,\"response_id\":\"P510ab7vNrenkdUP7MmsyQ0\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":83,\"candidates_tokens_details\":null,\"prompt_token_count\":594,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":336},{\"modality\":\"IMAGE\",\"token_count\":258}],\"thoughts_token_count\":644,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":1321,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1932-10-10\"],\"letter_title\":null,\"sender_persons\":[\"Jean Frey\"],\"receiver_persons\":[\"Dr. Max Vischer\"]}}}"}, "scoring": {"f1_macro": 0.54, "f1_micro": 0.54, "cost_summary": {"total_input_tokens": 44436, "total_output_tokens": 5548, "total_tokens": 49984, "input_cost_usd": 0.055545000000000004, "output_cost_usd": 0.05548000000000002, "total_cost_usd": 0.11102499999999998}}, "normalized_score": 54.0}, {"_id": {"$oid": "69d4eb12b877594bc5718a96"}, "test_id": "T0196", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-flash", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-05-15\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":[\"Basler Rheinschiffahrt - Aktiengesellschaft\"]}}", "model": "gemini-2.5-flash", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 594, "output_tokens": 52, "total_tokens": 2069, "input_cost_usd": 0.0001782, "output_cost_usd": 0.00013, "estimated_cost_usd": 0.0003082}, "duration": 7.0677759647369385, "timestamp": "2026-01-24T12:55:52.256316", "parsed": {"metadata": {"send_date": ["1928-05-15"], "letter_title": null, "sender_persons": null, "receiver_persons": ["Basler Rheinschiffahrt - Aktiengesellschaft"], "document_number": "letter36"}}, "conversation_id": "7b1bfeba-a916-4a41-9e6e-5cfbdd7e8757", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Sat, 24 Jan 2026 11:55:52 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=6917\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"video_metadata\":null,\"thought\":null,\"inline_data\":null,\"file_data\":null,\"thought_signature\":null,\"function_call\":null,\"code_execution_result\":null,\"executable_code\":null,\"function_response\":null,\"text\":\"{\\\"metadata\\\": {\\\"send_date\\\": [\\\"1928-05-15\\\"], \\\"letter_title\\\": null, \\\"sender_persons\\\": null, \\\"receiver_persons\\\": [\\\"Basler Rheinschiffahrt - Aktiengesellschaft\\\"]}}\"}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"url_context_metadata\":null,\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null}],\"create_time\":null,\"model_version\":\"gemini-2.5-flash\",\"prompt_feedback\":null,\"response_id\":\"SLN0aYm-C9bPnsEPvPi4sAY\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":52,\"candidates_tokens_details\":null,\"prompt_token_count\":594,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":336},{\"modality\":\"IMAGE\",\"token_count\":258}],\"thoughts_token_count\":1423,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":2069,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1928-05-15\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":[\"Basler Rheinschiffahrt - Aktiengesellschaft\"]}}}"}, "scoring": {"f1_macro": 0.52, "f1_micro": 0.52, "cost_summary": {"total_input_tokens": 44436, "total_output_tokens": 3735, "total_tokens": 48171, "input_cost_usd": 0.013330799999999995, "output_cost_usd": 0.009337500000000002, "total_cost_usd": 0.0226683}}, "normalized_score": 52.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b2e"}, "test_id": "T0255", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "qwen/qwen3-vl-30b-a3b-instruct", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-04-25\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"Basler Rheinschiffahrt A.G.\"],\"receiver_persons\":[\"Basel\"]}}", "model": "qwen/qwen3-vl-30b-a3b-instruct", "provider": "openrouter", "finish_reason": "stop", "usage": {"input_tokens": 3208, "output_tokens": 64, "total_tokens": 3272, "input_cost_usd": 0.0004812, "output_cost_usd": 3.84e-05, "estimated_cost_usd": 0.0005195999999999999}, "duration": 2.362961769104004, "timestamp": "2026-01-24T23:07:50.749982", "parsed": {"metadata": {"send_date": ["1928-04-25"], "letter_title": ["null"], "sender_persons": ["Basler Rheinschiffahrt A.G."], "receiver_persons": ["Basel"], "document_number": "letter28"}}, "conversation_id": "80594f27-992f-4ccc-9596-343042996dcd", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"gen-1769292468-jMJQO0ITOMoueoFv7Lo4\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1928-04-25\\\"],\\n \\\"letter_title\\\": [\\\"null\\\"],\\n \\\"sender_persons\\\": [\\\"Basler Rheinschiffahrt A.G.\\\"],\\n \\\"receiver_persons\\\": [\\\"Basel\\\"]\\n }\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-04-25\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"Basler Rheinschiffahrt A.G.\"],\"receiver_persons\":[\"Basel\"]}},\"reasoning\":null},\"native_finish_reason\":\"stop\"}],\"created\":1769292468,\"model\":\"qwen/qwen3-vl-30b-a3b-instruct\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":64,\"prompt_tokens\":3208,\"total_tokens\":3272,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":null,\"image_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0,\"video_tokens\":0},\"cost\":0.0006864,\"is_byok\":false,\"cost_details\":{\"upstream_inference_cost\":null,\"upstream_inference_prompt_cost\":0.0006416,\"upstream_inference_completions_cost\":0.0000448}},\"provider\":\"Phala\"}"}, "scoring": {"f1_macro": 0.47, "f1_micro": 0.53, "cost_summary": {"total_input_tokens": 108732, "total_output_tokens": 1918, "total_tokens": 110650, "input_cost_usd": 0.016309799999999996, "output_cost_usd": 0.0011507999999999998, "total_cost_usd": 0.0174606}}, "normalized_score": 47.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b78"}, "test_id": "T0101", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-opus-4-20250514", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\": {\"letter_title\": [null], \"send_date\": [\"1926-06-26\"], \"sender_persons\": [\"BASLER PERSONENSCHIFFFAHRTSGESELLSCHAFT BASEL\"], \"receiver_persons\": [\"Gesch\\u00e4ftsleitung der Internationalen Ausstellung f\\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel\", \"Direktion der Basler Rheinschiffahrt Aktiengesellschaft\", \"Herrn O. Ritter, Pr\\u00e4sident der Basler Rheinschiffahrt Aktiengesellschaft\"]}}", "model": "claude-opus-4-20250514", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 7176, "output_tokens": 179, "total_tokens": 7355, "input_cost_usd": 0.10764, "output_cost_usd": 0.013425, "estimated_cost_usd": 0.121065}, "duration": 7.510457515716553, "timestamp": "2026-01-24T11:18:23.365596", "parsed": {"metadata": {"letter_title": [null], "send_date": ["1926-06-26"], "sender_persons": ["BASLER PERSONENSCHIFFFAHRTSGESELLSCHAFT BASEL"], "receiver_persons": ["Gesch\u00e4ftsleitung der Internationalen Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel", "Direktion der Basler Rheinschiffahrt Aktiengesellschaft", "Herrn O. Ritter, Pr\u00e4sident der Basler Rheinschiffahrt Aktiengesellschaft"], "document_number": "letter08"}}, "conversation_id": "e8ae68a7-aba1-4c53-bfaf-b4d07413c2d9", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 3, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"msg_01FjHBSpjsGW9juLQfwFx2M8\",\"content\":[{\"id\":\"toolu_015QayFGDfuPWwvwrP1mLa3u\",\"input\":{\"metadata\":{\"letter_title\":[null],\"send_date\":[\"1926-06-26\"],\"sender_persons\":[\"BASLER PERSONENSCHIFFFAHRTSGESELLSCHAFT BASEL\"],\"receiver_persons\":[\"Gesch\u00e4ftsleitung der Internationalen Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel\",\"Direktion der Basler Rheinschiffahrt Aktiengesellschaft\",\"Herrn O. Ritter, Pr\u00e4sident der Basler Rheinschiffahrt Aktiengesellschaft\"],\"document_number\":\"letter08\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\"}],\"model\":\"claude-opus-4-20250514\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"input_tokens\":7176,\"output_tokens\":179,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.44, "f1_micro": 0.51, "cost_summary": {"total_input_tokens": 78390, "total_output_tokens": 2702, "total_tokens": 81092, "input_cost_usd": 1.1758499999999996, "output_cost_usd": 0.20265000000000005, "total_cost_usd": 1.3785}}, "normalized_score": 44.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b7c"}, "test_id": "T0174", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-medium-2505", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":null,\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":null}}", "model": "mistral-medium-2505", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 42, "total_tokens": 627, "input_cost_usd": 0.00023400000000000002, "output_cost_usd": 8.4e-05, "estimated_cost_usd": 0.00031800000000000003}, "duration": 1.266110897064209, "timestamp": "2026-01-24T11:42:00.420053", "parsed": {"metadata": {"letter_title": null, "send_date": null, "sender_persons": null, "receiver_persons": null, "document_number": "letter10"}}, "conversation_id": "424798cc-9699-4a27-bdf3-f8f1c34eff55", "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"0b61c171d17c4cef971b425747e424d5\",\"object\":\"chat.completion\",\"model\":\"mistral-medium-2505\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":42,\"total_tokens\":627,\"num_cached_tokens\":576},\"created\":1769251319,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"send_date\\\": null,\\n \\\"sender_persons\\\": null,\\n \\\"receiver_persons\\\": null\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 14625, "total_output_tokens": 1564, "total_tokens": 16189, "input_cost_usd": 0.0058499999999999976, "output_cost_usd": 0.003128, "total_cost_usd": 0.008977999999999998}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718b84"}, "test_id": "T0522", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-haiku-4-5-20251001", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1986-03-24\"],\"letter_title\":null,\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Herrn P. Christ - Wackernagel\",\"i/Fa. Paravicini, Christ & Co.\"]}}", "model": "claude-haiku-4-5-20251001", "provider": "anthropic", "finish_reason": "tool_use", "usage": {"input_tokens": 2787, "output_tokens": 123, "total_tokens": 2910, "input_cost_usd": 0.002787, "output_cost_usd": 0.0006150000000000001, "estimated_cost_usd": 0.003402}, "duration": 2.2031216621398926, "timestamp": "2026-01-24T17:44:43.631651", "parsed": {"metadata": {"letter_title": null, "send_date": ["1986-03-24"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Herrn P. Christ - Wackernagel", "i/Fa. Paravicini, Christ & Co."], "document_number": "letter03"}}, "conversation_id": "771b06f5-2747-499d-a565-9c7faa3c4bd5", "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"msg_01MWR21ABjrEY4xJhL6LFH84\",\"content\":[{\"id\":\"toolu_016GY9YUYdpwiZwthU52nUD3\",\"input\":{\"metadata\":{\"letter_title\":null,\"send_date\":[\"1986-03-24\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Herrn P. Christ - Wackernagel\",\"i/Fa. Paravicini, Christ & Co.\"],\"document_number\":\"letter03\"}},\"name\":\"extract_structured_data\",\"type\":\"tool_use\"}],\"model\":\"claude-haiku-4-5-20251001\",\"role\":\"assistant\",\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"type\":\"message\",\"usage\":{\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"input_tokens\":2787,\"output_tokens\":123,\"server_tool_use\":null,\"service_tier\":\"standard\"}}"}, "scoring": {"f1_macro": 0.43, "f1_micro": 0.44, "cost_summary": {"total_input_tokens": 222573, "total_output_tokens": 5987, "total_tokens": 228560, "input_cost_usd": 0.2225730000000003, "output_cost_usd": 0.029935000000000014, "total_cost_usd": 0.25250799999999995}}, "normalized_score": 43.0}, {"_id": {"$oid": "69d4eb12b877594bc5718b89"}, "test_id": "T0204", "benchmark": "business_letters", "date": "2026-01-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-flash-lite", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1935-08-16\"],\"letter_title\":[\"Basler Rheinschiffahrt Aktiengesellschaft\"],\"sender_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft\"],\"receiver_persons\":[\"Basler Personenschiffahrts-Gesellschaft\"]}}", "model": "gemini-2.5-flash-lite", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 594, "output_tokens": 109, "total_tokens": 703, "input_cost_usd": 5.940000000000001e-05, "output_cost_usd": 4.36e-05, "estimated_cost_usd": 0.00010300000000000001}, "duration": 1.0664646625518799, "timestamp": "2026-01-24T13:34:41.126678", "parsed": {"metadata": {"send_date": ["1935-08-16"], "letter_title": ["Basler Rheinschiffahrt Aktiengesellschaft"], "sender_persons": ["Basler Rheinschiffahrt Aktiengesellschaft"], "receiver_persons": ["Basler Personenschiffahrts-Gesellschaft"], "document_number": "letter64"}}, "conversation_id": "e61ed70f-143a-4267-ac1e-8e5c00cab2e1", "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Sat, 24 Jan 2026 12:34:41 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=922\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"video_metadata\":null,\"thought\":null,\"inline_data\":null,\"file_data\":null,\"thought_signature\":null,\"function_call\":null,\"code_execution_result\":null,\"executable_code\":null,\"function_response\":null,\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\n \\\"1935-08-16\\\"\\n ],\\n \\\"letter_title\\\": [\\n \\\"Basler Rheinschiffahrt Aktiengesellschaft\\\"\\n ],\\n \\\"sender_persons\\\": [\\n \\\"Basler Rheinschiffahrt Aktiengesellschaft\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"Basler Personenschiffahrts-Gesellschaft\\\"\\n ]\\n }\\n}\"}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"url_context_metadata\":null,\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null}],\"create_time\":null,\"model_version\":\"gemini-2.5-flash-lite\",\"prompt_feedback\":null,\"response_id\":\"Ybx0affTAtzskdUPucnuyQM\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":109,\"candidates_tokens_details\":null,\"prompt_token_count\":594,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":336},{\"modality\":\"IMAGE\",\"token_count\":258}],\"thoughts_token_count\":null,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":703,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1935-08-16\"],\"letter_title\":[\"Basler Rheinschiffahrt Aktiengesellschaft\"],\"sender_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft\"],\"receiver_persons\":[\"Basler Personenschiffahrts-Gesellschaft\"]}}}"}, "scoring": {"f1_macro": 0.44, "f1_micro": 0.44, "cost_summary": {"total_input_tokens": 44436, "total_output_tokens": 6312, "total_tokens": 50748, "input_cost_usd": 0.004443600000000001, "output_cost_usd": 0.0025248000000000002, "total_cost_usd": 0.006968400000000001}}, "normalized_score": 44.0}, {"_id": {"$oid": "69d4eb12b877594bc5718a4b"}, "test_id": "T0405", "benchmark": "business_letters", "date": "2025-11-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5.1-2025-11-13", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-04-25\"],\"letter_title\":[\"\"],\"sender_persons\":[\"\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.G.\"]}}", "model": "gpt-5.1-2025-11-13", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 1398, "output_tokens": 53, "total_tokens": 1451}, "duration": 4.159851551055908, "timestamp": "2025-11-25T10:01:58.252434", "parsed": {"metadata": {"send_date": ["1928-04-25"], "letter_title": [""], "sender_persons": [""], "receiver_persons": ["Basler Rheinschiffahrt A.G."], "document_number": "letter28"}}, "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-CfjDouwoWBATWyJoF9e57wzMwjeOY\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1928-04-25\\\"],\\\"letter_title\\\":[\\\"\\\"],\\\"sender_persons\\\":[\\\"\\\"],\\\"receiver_persons\\\":[\\\"Basler Rheinschiffahrt A.G.\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-04-25\"],\"letter_title\":[\"\"],\"sender_persons\":[\"\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.G.\"]}}}}],\"created\":1764061316,\"model\":\"gpt-5.1-2025-11-13\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":53,\"prompt_tokens\":1398,\"total_tokens\":1451,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":1280}}}"}, "scoring": {"f1_macro": 0.48, "f1_micro": 0.57, "cost_summary": {"total_input_tokens": 44050, "total_output_tokens": 1475, "total_tokens": 45525, "input_cost_usd": 0.05506249999999998, "output_cost_usd": 0.014750000000000001, "total_cost_usd": 0.06981249999999999}}, "normalized_score": 48.0}, {"_id": {"$oid": "69d4eb12b877594bc5718a4d"}, "test_id": "T0438", "benchmark": "business_letters", "date": "2025-11-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-small-2506", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":null,\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":null}}", "model": "mistral-small-2506", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 42, "total_tokens": 627, "input_cost_usd": 5.8500000000000006e-05, "output_cost_usd": 1.26e-05, "estimated_cost_usd": 7.110000000000001e-05}, "duration": 1.1960663795471191, "timestamp": "2025-11-25T10:14:35.664295", "parsed": {"metadata": {"letter_title": null, "send_date": null, "sender_persons": null, "receiver_persons": null, "document_number": "letter02"}}, "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 1, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"e20fa54e0b574656b1c1e33849ffa9ab\",\"object\":\"chat.completion\",\"model\":\"mistral-small-2506\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":42,\"total_tokens\":627},\"created\":1764062075,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"send_date\\\": null,\\n \\\"sender_persons\\\": null,\\n \\\"receiver_persons\\\": null\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 18720, "total_output_tokens": 1436, "total_tokens": 20156, "input_cost_usd": 0.001871999999999999, "output_cost_usd": 0.0004308000000000001, "total_cost_usd": 0.0023028}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718a50"}, "test_id": "T0404", "benchmark": "business_letters", "date": "2025-11-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5.1-2025-11-13", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1935-08-17\"],\"letter_title\":[\"\"],\"sender_persons\":[\"\"],\"receiver_persons\":[\"Fritz Ritter\"]}}", "model": "gpt-5.1-2025-11-13", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 1398, "output_tokens": 46, "total_tokens": 1444}, "duration": 3.156399726867676, "timestamp": "2025-11-25T10:00:54.520793", "parsed": {"metadata": {"send_date": ["1935-08-17"], "letter_title": [""], "sender_persons": [""], "receiver_persons": ["Fritz Ritter"], "document_number": "letter65"}}, "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-CfjCmsbYxjV2G1ox5z8N9zEtMSHRY\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1935-08-17\\\"],\\\"letter_title\\\":[\\\"\\\"],\\\"sender_persons\\\":[\\\"\\\"],\\\"receiver_persons\\\":[\\\"Fritz Ritter\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1935-08-17\"],\"letter_title\":[\"\"],\"sender_persons\":[\"\"],\"receiver_persons\":[\"Fritz Ritter\"]}}}}],\"created\":1764061252,\"model\":\"gpt-5.1-2025-11-13\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":46,\"prompt_tokens\":1398,\"total_tokens\":1444,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0}}}"}, "scoring": {"f1_macro": 0.53, "f1_micro": 0.55, "cost_summary": {"total_input_tokens": 116996, "total_output_tokens": 3482, "total_tokens": 120478, "input_cost_usd": 0.14624500000000007, "output_cost_usd": 0.034820000000000004, "total_cost_usd": 0.18106499999999995}}, "normalized_score": 53.0}, {"_id": {"$oid": "69d4eb12b877594bc5718a51"}, "test_id": "T0437", "benchmark": "business_letters", "date": "2025-11-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-small-2506", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"null\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"null\"]}}", "model": "mistral-small-2506", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 46, "total_tokens": 631, "input_cost_usd": 5.8500000000000006e-05, "output_cost_usd": 1.38e-05, "estimated_cost_usd": 7.230000000000001e-05}, "duration": 0.6165597438812256, "timestamp": "2025-11-25T10:14:29.012442", "parsed": {"metadata": {"letter_title": ["null"], "send_date": ["null"], "sender_persons": ["null"], "receiver_persons": ["null"], "document_number": "letter49"}}, "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"6aafd7fb6147430a8bac75fd44bfe72b\",\"object\":\"chat.completion\",\"model\":\"mistral-small-2506\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":46,\"total_tokens\":631},\"created\":1764062068,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": [\\\"null\\\"],\\n \\\"send_date\\\": [\\\"null\\\"],\\n \\\"sender_persons\\\": [\\\"null\\\"],\\n \\\"receiver_persons\\\": [\\\"null\\\"]\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 14625, "total_output_tokens": 1110, "total_tokens": 15735, "input_cost_usd": 0.0014624999999999994, "output_cost_usd": 0.000333, "total_cost_usd": 0.0017954999999999996}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718a52"}, "test_id": "T0436", "benchmark": "business_letters", "date": "2025-11-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-small-2506", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":null,\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":null}}", "model": "mistral-small-2506", "provider": "mistral", "finish_reason": "stop", "usage": {"input_tokens": 585, "output_tokens": 42, "total_tokens": 627, "input_cost_usd": 5.8500000000000006e-05, "output_cost_usd": 1.26e-05, "estimated_cost_usd": 7.110000000000001e-05}, "duration": 0.8892834186553955, "timestamp": "2025-11-25T10:13:32.556055", "parsed": {"metadata": {"letter_title": null, "send_date": null, "sender_persons": null, "receiver_persons": null, "document_number": "letter05"}}, "score": {"send_date_tp": 0, "send_date_fp": 0, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 1}, "raw_response": "{\"id\":\"26e4129ed8e9468887d7feed913cb8cc\",\"object\":\"chat.completion\",\"model\":\"mistral-small-2506\",\"usage\":{\"prompt_tokens\":585,\"completion_tokens\":42,\"total_tokens\":627},\"created\":1764062011,\"choices\":[{\"index\":0,\"message\":{\"content\":\"{\\n \\\"metadata\\\": {\\n \\\"letter_title\\\": null,\\n \\\"send_date\\\": null,\\n \\\"sender_persons\\\": null,\\n \\\"receiver_persons\\\": null\\n }\\n}\",\"tool_calls\":null,\"prefix\":false,\"role\":\"assistant\"},\"finish_reason\":\"stop\"}]}"}, "scoring": {"f1_macro": 0.0, "f1_micro": 0.0, "cost_summary": {"total_input_tokens": 33345, "total_output_tokens": 2528, "total_tokens": 35873, "input_cost_usd": 0.003334499999999998, "output_cost_usd": 0.0007584000000000001, "total_cost_usd": 0.0040929}}, "normalized_score": 0}, {"_id": {"$oid": "69d4eb12b877594bc5718a60"}, "test_id": "T0406", "benchmark": "business_letters", "date": "2025-11-25", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5.1-2025-11-13", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-04-26\"],\"letter_title\":[\"\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Max Oettinger\"]}}", "model": "gpt-5.1-2025-11-13", "provider": "openai", "finish_reason": "stop", "usage": {"input_tokens": 1398, "output_tokens": 58, "total_tokens": 1456}, "duration": 4.0931878089904785, "timestamp": "2025-11-25T10:04:33.053468", "parsed": {"metadata": {"send_date": ["1928-04-26"], "letter_title": [""], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Max Oettinger"], "document_number": "letter29"}}, "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 2, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"id\":\"chatcmpl-CfjGITfIWvTWeOSFEpfYdlroamY5M\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"metadata\\\":{\\\"send_date\\\":[\\\"1928-04-26\\\"],\\\"letter_title\\\":[\\\"\\\"],\\\"sender_persons\\\":[\\\"Basler Rheinschiffahrt-Aktiengesellschaft\\\"],\\\"receiver_persons\\\":[\\\"Max Oettinger\\\"]}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":[],\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"metadata\":{\"send_date\":[\"1928-04-26\"],\"letter_title\":[\"\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Max Oettinger\"]}}}}],\"created\":1764061470,\"model\":\"gpt-5.1-2025-11-13\",\"object\":\"chat.completion\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":58,\"prompt_tokens\":1398,\"total_tokens\":1456,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":1280}}}"}, "scoring": {"f1_macro": 0.59, "f1_micro": 0.54, "cost_summary": {"total_input_tokens": 72946, "total_output_tokens": 2024, "total_tokens": 74970, "input_cost_usd": 0.09118249999999997, "output_cost_usd": 0.020239999999999998, "total_cost_usd": 0.11142250000000001}}, "normalized_score": 59.0}, {"_id": {"$oid": "69d4eb12b877594bc5718a3b"}, "test_id": "T0196", "benchmark": "business_letters", "date": "2025-11-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-flash", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1928-05-15\"],\"letter_title\":[\"Denial of Responsibility for Article by Jean Richard Frey\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"null\"]}}", "model": "gemini-2.5-flash", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 594, "output_tokens": 82, "total_tokens": 3758, "input_cost_usd": 0.0001782, "output_cost_usd": 0.000205, "estimated_cost_usd": 0.0003832}, "duration": 17.6065194606781, "timestamp": "2025-11-24T20:32:05.627891", "parsed": {"metadata": {"send_date": ["1928-05-15"], "letter_title": ["Denial of Responsibility for Article by Jean Richard Frey"], "sender_persons": ["null"], "receiver_persons": ["null"], "document_number": "letter36"}}, "score": {"send_date_tp": 1, "send_date_fp": 0, "send_date_fn": 0, "sender_persons_tp": 0, "sender_persons_fp": 0, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Mon, 24 Nov 2025 19:32:06 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=17445\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"video_metadata\":null,\"thought\":null,\"inline_data\":null,\"file_data\":null,\"thought_signature\":null,\"function_call\":null,\"code_execution_result\":null,\"executable_code\":null,\"function_response\":null,\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1928-05-15\\\"],\\n \\\"letter_title\\\": [\\\"Denial of Responsibility for Article by Jean Richard Frey\\\"],\\n \\\"sender_persons\\\": [\\n \\\"null\\\"\\n ],\\n \\\"receiver_persons\\\": [\\n \\\"null\\\"\\n ]\\n }\\n}\"}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"url_context_metadata\":null,\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null}],\"create_time\":null,\"model_version\":\"gemini-2.5-flash\",\"prompt_feedback\":null,\"response_id\":\"trIkaY-8CJL-vdIP9pyLuQY\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":82,\"candidates_tokens_details\":null,\"prompt_token_count\":594,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":336},{\"modality\":\"IMAGE\",\"token_count\":258}],\"thoughts_token_count\":3082,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":3758,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1928-05-15\"],\"letter_title\":[\"Denial of Responsibility for Article by Jean Richard Frey\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"null\"]}}}"}, "scoring": {"f1_macro": 0.54, "f1_micro": 0.52, "cost_summary": {"total_input_tokens": 44436, "total_output_tokens": 3764, "total_tokens": 48200, "input_cost_usd": 0.013330799999999995, "output_cost_usd": 0.009410000000000002, "total_cost_usd": 0.022740800000000005}}, "normalized_score": 54.0}, {"_id": {"$oid": "69d4eb12b877594bc5718a3e"}, "test_id": "T0198", "benchmark": "business_letters", "date": "2025-11-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-flash", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1964-06-28\"],\"letter_title\":null,\"sender_persons\":[\"Fritz Steiger\",\"Max Vischer\"],\"receiver_persons\":[\"P. Christ-Wackernagel\"]}}", "model": "gemini-2.5-flash", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 852, "output_tokens": 75, "total_tokens": 1200, "input_cost_usd": 0.0002556, "output_cost_usd": 0.00018749999999999998, "estimated_cost_usd": 0.0004431}, "duration": 2.6199350357055664, "timestamp": "2025-11-24T20:40:29.687780", "parsed": {"metadata": {"send_date": ["1964-06-28"], "letter_title": null, "sender_persons": ["Fritz Steiger", "Max Vischer"], "receiver_persons": ["P. Christ-Wackernagel"], "document_number": "letter09"}}, "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 1, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 1, "receiver_persons_fp": 0, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Mon, 24 Nov 2025 19:40:30 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=2309\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"video_metadata\":null,\"thought\":null,\"inline_data\":null,\"file_data\":null,\"thought_signature\":null,\"function_call\":null,\"code_execution_result\":null,\"executable_code\":null,\"function_response\":null,\"text\":\"{\\n \\\"metadata\\\": {\\n \\\"send_date\\\": [\\\"1964-06-28\\\"],\\n \\\"letter_title\\\": null,\\n \\\"sender_persons\\\": [\\\"Fritz Steiger\\\", \\\"Max Vischer\\\"],\\n \\\"receiver_persons\\\": [\\\"P. Christ-Wackernagel\\\"]\\n }\\n}\"}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"url_context_metadata\":null,\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null}],\"create_time\":null,\"model_version\":\"gemini-2.5-flash\",\"prompt_feedback\":null,\"response_id\":\"rrQkaYHLC6u7xN8PgfWXyQM\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":75,\"candidates_tokens_details\":null,\"prompt_token_count\":852,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":336},{\"modality\":\"IMAGE\",\"token_count\":516}],\"thoughts_token_count\":273,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":1200,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1964-06-28\"],\"letter_title\":null,\"sender_persons\":[\"Fritz Steiger\",\"Max Vischer\"],\"receiver_persons\":[\"P. Christ-Wackernagel\"]}}}"}, "scoring": {"f1_macro": 0.51, "f1_micro": 0.48, "cost_summary": {"total_input_tokens": 27006, "total_output_tokens": 2225, "total_tokens": 29231, "input_cost_usd": 0.008101799999999998, "output_cost_usd": 0.0055625, "total_cost_usd": 0.013664299999999996}}, "normalized_score": 51.0}, {"_id": {"$oid": "69d4eb12b877594bc5718a3f"}, "test_id": "T0197", "benchmark": "business_letters", "date": "2025-11-24", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-flash", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"text": "{\"metadata\":{\"send_date\":[\"1933-04-04\"],\"letter_title\":[\"BESCHREIEN\"],\"sender_persons\":[\"Basler Personenschifffahrtgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschifffahrt-Aktiengesellschaft\"]}}", "model": "gemini-2.5-flash", "provider": "genai", "finish_reason": "STOP", "usage": {"input_tokens": 852, "output_tokens": 65, "total_tokens": 1186, "input_cost_usd": 0.0002556, "output_cost_usd": 0.0001625, "estimated_cost_usd": 0.00041809999999999997}, "duration": 2.368257761001587, "timestamp": "2025-11-24T21:56:00.233052", "parsed": {"metadata": {"send_date": ["1933-04-04"], "letter_title": ["BESCHREIEN"], "sender_persons": ["Basler Personenschifffahrtgesellschaft"], "receiver_persons": ["Basler Rheinschifffahrt-Aktiengesellschaft"], "document_number": "letter24"}}, "score": {"send_date_tp": 0, "send_date_fp": 1, "send_date_fn": 1, "sender_persons_tp": 0, "sender_persons_fp": 1, "sender_persons_fn": 0, "receiver_persons_tp": 0, "receiver_persons_fp": 1, "receiver_persons_fn": 0}, "raw_response": "{\"sdk_http_response\":{\"headers\":{\"content-type\":\"application/json; charset=UTF-8\",\"vary\":\"Origin, X-Origin, Referer\",\"content-encoding\":\"gzip\",\"date\":\"Mon, 24 Nov 2025 20:56:00 GMT\",\"server\":\"scaffolding on HTTPServer2\",\"x-xss-protection\":\"0\",\"x-frame-options\":\"SAMEORIGIN\",\"x-content-type-options\":\"nosniff\",\"server-timing\":\"gfet4t7; dur=2069\",\"alt-svc\":\"h3=\\\":443\\\"; ma=2592000,h3-29=\\\":443\\\"; ma=2592000\",\"transfer-encoding\":\"chunked\"},\"body\":null},\"candidates\":[{\"content\":{\"parts\":[{\"video_metadata\":null,\"thought\":null,\"inline_data\":null,\"file_data\":null,\"thought_signature\":null,\"function_call\":null,\"code_execution_result\":null,\"executable_code\":null,\"function_response\":null,\"text\":\"{\\\"metadata\\\": {\\\"send_date\\\": [\\\"1933-04-04\\\"], \\\"letter_title\\\": [\\\"BESCHREIEN\\\"], \\\"sender_persons\\\": [\\\"Basler Personenschifffahrtgesellschaft\\\"], \\\"receiver_persons\\\": [\\\"Basler Rheinschifffahrt-Aktiengesellschaft\\\"]}}\"}],\"role\":\"model\"},\"citation_metadata\":null,\"finish_message\":null,\"token_count\":null,\"finish_reason\":\"STOP\",\"url_context_metadata\":null,\"avg_logprobs\":null,\"grounding_metadata\":null,\"index\":0,\"logprobs_result\":null,\"safety_ratings\":null}],\"create_time\":null,\"model_version\":\"gemini-2.5-flash\",\"prompt_feedback\":null,\"response_id\":\"YMYkae7JMvzn7M8Pns3VyQ4\",\"usage_metadata\":{\"cache_tokens_details\":null,\"cached_content_token_count\":null,\"candidates_token_count\":65,\"candidates_tokens_details\":null,\"prompt_token_count\":852,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":336},{\"modality\":\"IMAGE\",\"token_count\":516}],\"thoughts_token_count\":269,\"tool_use_prompt_token_count\":null,\"tool_use_prompt_tokens_details\":null,\"total_token_count\":1186,\"traffic_type\":null},\"automatic_function_calling_history\":[],\"parsed\":{\"metadata\":{\"send_date\":[\"1933-04-04\"],\"letter_title\":[\"BESCHREIEN\"],\"sender_persons\":[\"Basler Personenschifffahrtgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschifffahrt-Aktiengesellschaft\"]}}}"}, "scoring": {"f1_macro": 0.45, "f1_micro": 0.52, "cost_summary": {"total_input_tokens": 17430, "total_output_tokens": 1729, "total_tokens": 19159, "input_cost_usd": 0.005228999999999998, "output_cost_usd": 0.004322500000000002, "total_cost_usd": 0.009551500000000001}}, "normalized_score": 45.0}, {"_id": {"$oid": "69d4eb12b877594bc571899f"}, "test_id": "T0245", "benchmark": "business_letters", "date": "2025-10-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "qwen/qwen3-vl-8b-thinking", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openrouter", "model": "qwen/qwen3-vl-8b-thinking", "duration": 2.1810593605041504, "timestamp": "2025-10-17T22:51:05.800209", "text": "", "raw_response": {"id": "gen-1760734264-xYTNlJAZYvDkvMXe4hVd", "model": "qwen/qwen3-vl-8b-thinking", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "", "role": "assistant"}}], "usage": {"prompt_tokens": 1769, "completion_tokens": 68, "total_tokens": 1837}}, "usage": {"input_tokens": 1769, "output_tokens": 68, "total_tokens": 1837}, "error": "JSONDecodeError", "error_message": "Expecting value: line 1 column 1 (char 0)", "finish_reason": "stop"}, "scoring": {"f1_macro": 0.12, "f1_micro": 0.1, "cost_summary": {"total_input_tokens": 101496, "total_output_tokens": 19082, "total_tokens": 120578, "input_cost_usd": 0.018269, "output_cost_usd": 0.040072, "total_cost_usd": 0.058341, "pricing_date": "2025-10-17", "input_price_per_million": 0.18, "output_price_per_million": 2.1}}, "normalized_score": 12.0}, {"_id": {"$oid": "69d4eb12b877594bc57189a1"}, "test_id": "T0250", "benchmark": "business_letters", "date": "2025-10-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "meta-llama/llama-4-maverick", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openrouter", "model": "meta-llama/llama-4-maverick", "duration": 2.816835403442383, "timestamp": "2025-10-17T22:44:38.126487", "parsed": {"metadata": {"send_date": ["1932-10-15"], "letter_title": ["Darlehen f\u00fcr den Bau des neuen Personenschiffes"], "sender_persons": ["Basler Rheinschiffahrt Aktiengesellschaft"], "receiver_persons": ["Dr. Max Vischer"]}}, "text": "", "raw_response": {"id": "gen-1760733875-0iT3GbkXDUYMQ3B3ueDk", "model": "meta-llama/llama-4-maverick", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1932-10-15\"],\n \"letter_title\": [\"Darlehen f\u00fcr den Bau des neuen Personenschiffes\"],\n \"sender_persons\": [\"Basler Rheinschiffahrt Aktiengesellschaft\"],\n \"receiver_persons\": [\"Dr. Max Vischer\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 4098, "completion_tokens": 75, "total_tokens": 4173}}, "usage": {"input_tokens": 4098, "output_tokens": 75, "total_tokens": 4173}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.48, "f1_micro": 0.45, "cost_summary": {"total_input_tokens": 128746, "total_output_tokens": 1986, "total_tokens": 130732, "input_cost_usd": 0.019312, "output_cost_usd": 0.001192, "total_cost_usd": 0.020504, "pricing_date": "2025-10-17", "input_price_per_million": 0.15, "output_price_per_million": 0.6}}, "normalized_score": 48.0}, {"_id": {"$oid": "69d4eb12b877594bc57189a3"}, "test_id": "T0243", "benchmark": "business_letters", "date": "2025-10-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "qwen/qwen3-vl-8b-thinking", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openrouter", "model": "qwen/qwen3-vl-8b-thinking", "duration": 2.3174095153808594, "timestamp": "2025-10-17T22:43:31.714805", "text": "", "raw_response": {"id": "gen-1760733809-SVoff4O7dIaGDmtRlVRX", "model": "qwen/qwen3-vl-8b-thinking", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "", "role": "assistant"}}], "usage": {"prompt_tokens": 3217, "completion_tokens": 91, "total_tokens": 3308}}, "usage": {"input_tokens": 3217, "output_tokens": 91, "total_tokens": 3308}, "error": "JSONDecodeError", "error_message": "Expecting value: line 1 column 1 (char 0)", "finish_reason": "stop"}, "scoring": {"f1_macro": 0.07, "f1_micro": 0.06, "cost_summary": {"total_input_tokens": 160201, "total_output_tokens": 13956, "total_tokens": 174157, "input_cost_usd": 0.028836, "output_cost_usd": 0.029308, "total_cost_usd": 0.058144, "pricing_date": "2025-10-17", "input_price_per_million": 0.18, "output_price_per_million": 2.1}}, "normalized_score": 7.000000000000001}, {"_id": {"$oid": "69d4eb12b877594bc57189a4"}, "test_id": "T0244", "benchmark": "business_letters", "date": "2025-10-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "qwen/qwen3-vl-8b-thinking", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openrouter", "model": "qwen/qwen3-vl-8b-thinking", "duration": 1.7003304958343506, "timestamp": "2025-10-17T22:46:52.690923", "text": "", "raw_response": {"id": "gen-1760734011-iJ7xozEjIOmvSR0JgnYz", "model": "qwen/qwen3-vl-8b-thinking", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "", "role": "assistant"}}], "usage": {"prompt_tokens": 1769, "completion_tokens": 68, "total_tokens": 1837}}, "usage": {"input_tokens": 1769, "output_tokens": 68, "total_tokens": 1837}, "error": "JSONDecodeError", "error_message": "Expecting value: line 1 column 1 (char 0)", "finish_reason": "stop"}, "scoring": {"f1_macro": 0.29, "f1_micro": 0.19, "cost_summary": {"total_input_tokens": 58705, "total_output_tokens": 11030, "total_tokens": 69735, "input_cost_usd": 0.010567, "output_cost_usd": 0.023163, "total_cost_usd": 0.03373, "pricing_date": "2025-10-17", "input_price_per_million": 0.18, "output_price_per_million": 2.1}}, "normalized_score": 28.999999999999996}, {"_id": {"$oid": "69d4eb12b877594bc57189a5"}, "test_id": "T0249", "benchmark": "business_letters", "date": "2025-10-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "meta-llama/llama-4-maverick", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openrouter", "model": "meta-llama/llama-4-maverick", "duration": 1.3728344440460205, "timestamp": "2025-10-17T22:43:21.434412", "parsed": {"metadata": {"send_date": ["1932-09-23"], "letter_title": ["null"], "sender_persons": ["null"], "receiver_persons": ["Direktion der Basler Rheinschiffahrts-Aktiengesellschaft"]}}, "text": "", "raw_response": {"id": "gen-1760733800-vurLdkxO5egTSMEfmU0i", "model": "meta-llama/llama-4-maverick", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1932-09-23\"],\n \"letter_title\": [\"null\"],\n \"sender_persons\": [\"null\"],\n \"receiver_persons\": [\"Direktion der Basler Rheinschiffahrts-Aktiengesellschaft\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 2211, "completion_tokens": 62, "total_tokens": 2273}}, "usage": {"input_tokens": 2211, "output_tokens": 62, "total_tokens": 2273}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.38, "f1_micro": 0.47, "cost_summary": {"total_input_tokens": 73930, "total_output_tokens": 1491, "total_tokens": 75421, "input_cost_usd": 0.011089, "output_cost_usd": 0.000895, "total_cost_usd": 0.011984, "pricing_date": "2025-10-17", "input_price_per_million": 0.15, "output_price_per_million": 0.6}}, "normalized_score": 38.0}, {"_id": {"$oid": "69d4eb12b877594bc57189aa"}, "test_id": "T0248", "benchmark": "business_letters", "date": "2025-10-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openrouter", "model": "meta-llama/llama-4-maverick", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openrouter", "model": "meta-llama/llama-4-maverick", "duration": 3.0641567707061768, "timestamp": "2025-10-17T22:41:04.811679", "parsed": {"metadata": {"send_date": ["1928-05-05"], "letter_title": ["null"], "sender_persons": ["Schriftleitung der Zeitschrift 'Die Rheinquellen'"], "receiver_persons": ["Basler Rheinschiffahrts-A.G."]}}, "text": "", "raw_response": {"id": "gen-1760733662-hFhLqGeWwHQ92x1sRDPw", "model": "meta-llama/llama-4-maverick", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1928-05-05\"],\n \"letter_title\": [\"null\"],\n \"sender_persons\": [\"Schriftleitung der Zeitschrift 'Die Rheinquellen'\"],\n \"receiver_persons\": [\"Basler Rheinschiffahrts-A.G.\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 2210, "completion_tokens": 67, "total_tokens": 2277}}, "usage": {"input_tokens": 2210, "output_tokens": 67, "total_tokens": 2277}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.46, "f1_micro": 0.47, "cost_summary": {"total_input_tokens": 203693, "total_output_tokens": 3574, "total_tokens": 207267, "input_cost_usd": 0.030554, "output_cost_usd": 0.002144, "total_cost_usd": 0.032698, "pricing_date": "2025-10-17", "input_price_per_million": 0.15, "output_price_per_million": 0.6}}, "normalized_score": 46.0}, {"_id": {"$oid": "69d4eb12b877594bc57189ac"}, "test_id": "T0240", "benchmark": "business_letters", "date": "2025-10-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "scicore", "model": "GLM-4.5V-FP8", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "scicore", "model": "GLM-4.5V-FP8", "duration": 0.9497272968292236, "timestamp": "2025-10-17T15:15:52.885393", "parsed": {"metadata": {"send_date": ["1928-04-26"], "letter_title": ["Confirmation of Receipt"], "sender_persons": ["Basler Rheinschifffahrt-Aktiengesellschaft"], "receiver_persons": ["Herrn Max Oettinger, Verkehrsbureau, Basel"]}}, "text": "", "raw_response": {"id": "chatcmpl-0a273fe85dc64e62ac5db8514eb98c6d", "model": "hosted_vllm/GLM-4.5V-FP8", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\"metadata\": {\"send_date\": [\"1928-04-26\"], \"letter_title\": [\"Confirmation of Receipt\"], \"sender_persons\": [\"Basler Rheinschifffahrt-Aktiengesellschaft\"], \"receiver_persons\": [\"Herrn Max Oettinger, Verkehrsbureau, Basel\"]}}", "role": "assistant"}}], "usage": {"prompt_tokens": 1280, "completion_tokens": 68, "total_tokens": 1348}}, "usage": {"input_tokens": 1280, "output_tokens": 68, "total_tokens": 1348}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.5, "f1_micro": 0.46, "cost_summary": {"total_input_tokens": 70844, "total_output_tokens": 2257, "total_tokens": 73101, "input_cost_usd": 0.0, "output_cost_usd": 0.0, "total_cost_usd": 0.0, "pricing_date": "2025-10-17", "input_price_per_million": 0.0, "output_price_per_million": 0.0}}, "normalized_score": 50.0}, {"_id": {"$oid": "69d4eb12b877594bc57189ad"}, "test_id": "T0238", "benchmark": "business_letters", "date": "2025-10-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "scicore", "model": "GLM-4.5V-FP8", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "scicore", "model": "GLM-4.5V-FP8", "duration": 1.3323974609375, "timestamp": "2025-10-17T15:13:54.440675", "parsed": {"metadata": {"send_date": ["1926-03-24"], "letter_title": ["Letter from Basler Rheinschifffahrt-Aktiengesellschaft"], "sender_persons": ["Basler Rheinschifffahrt-Aktiengesellschaft"], "receiver_persons": ["Herrn P. Christ - Wackernagel"]}}, "text": "", "raw_response": {"id": "chatcmpl-87c3cf68522f4d7e8de8ad3a94a00a65", "model": "hosted_vllm/GLM-4.5V-FP8", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\"metadata\": {\"send_date\": [\"1926-03-24\"], \"letter_title\": [\"Letter from Basler Rheinschifffahrt-Aktiengesellschaft\"], \"sender_persons\": [\"Basler Rheinschifffahrt-Aktiengesellschaft\"], \"receiver_persons\": [\"Herrn P. Christ - Wackernagel\"]}}", "role": "assistant"}}], "usage": {"prompt_tokens": 1280, "completion_tokens": 82, "total_tokens": 1362}}, "usage": {"input_tokens": 1280, "output_tokens": 82, "total_tokens": 1362}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.48, "f1_micro": 0.5, "cost_summary": {"total_input_tokens": 112484, "total_output_tokens": 3815, "total_tokens": 116299, "input_cost_usd": 0.0, "output_cost_usd": 0.0, "total_cost_usd": 0.0, "pricing_date": "2025-10-17", "input_price_per_million": 0.0, "output_price_per_million": 0.0}}, "normalized_score": 48.0}, {"_id": {"$oid": "69d4eb12b877594bc57189b0"}, "test_id": "T0239", "benchmark": "business_letters", "date": "2025-10-17", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "scicore", "model": "GLM-4.5V-FP8", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "scicore", "model": "GLM-4.5V-FP8", "duration": 0.8065743446350098, "timestamp": "2025-10-17T15:15:27.945217", "parsed": {"metadata": {"send_date": ["1932-09-09"], "letter_title": ["null"], "sender_persons": ["null"], "receiver_persons": ["Basler Rheinschifffahrts-Aktiengesellschaft Direktion"]}}, "text": "", "raw_response": {"id": "chatcmpl-5629148b5be9406da3d0232518b335d3", "model": "hosted_vllm/GLM-4.5V-FP8", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\"metadata\": {\"send_date\": [\"1932-09-09\"], \"letter_title\": [\"null\"], \"sender_persons\": [\"null\"], \"receiver_persons\": [\"Basler Rheinschifffahrts-Aktiengesellschaft Direktion\"]}}", "role": "assistant"}}], "usage": {"prompt_tokens": 1280, "completion_tokens": 57, "total_tokens": 1337}}, "usage": {"input_tokens": 1280, "output_tokens": 57, "total_tokens": 1337}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.46, "f1_micro": 0.57, "cost_summary": {"total_input_tokens": 41640, "total_output_tokens": 1528, "total_tokens": 43168, "input_cost_usd": 0.0, "output_cost_usd": 0.0, "total_cost_usd": 0.0, "pricing_date": "2025-10-17", "input_price_per_million": 0.0, "output_price_per_million": 0.0}}, "normalized_score": 46.0}, {"_id": {"$oid": "69d4eb12b877594bc571896c"}, "test_id": "T0134", "benchmark": "business_letters", "date": "2025-10-01", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "o3", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "o3", "duration": 13.008349180221558, "timestamp": "2025-10-01T00:15:40.458257", "parsed": {"metadata": {"send_date": ["1928-05-10"], "letter_title": ["Betr. Abrechnung"], "sender_persons": null, "receiver_persons": null}}, "text": "", "raw_response": {"id": "chatcmpl-CLcv2yhYIPrbQmIL77akwytOElEa6", "model": "o3-2025-04-16", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\"metadata\":{\"send_date\":[\"1928-05-10\"],\"letter_title\":[\"Betr. Abrechnung\"],\"sender_persons\":null,\"receiver_persons\":null}}", "role": "assistant"}}], "usage": {"prompt_tokens": 1163, "completion_tokens": 505, "total_tokens": 1668}}, "usage": {"input_tokens": 1163, "output_tokens": 505, "total_tokens": 1668}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.6, "f1_micro": 0.63, "cost_summary": {"total_input_tokens": 93966, "total_output_tokens": 39670, "total_tokens": 133636, "input_cost_usd": 0.187932, "output_cost_usd": 0.31736, "total_cost_usd": 0.505292, "pricing_date": "2025-10-01", "input_price_per_million": 2.0, "output_price_per_million": 8.0}}, "normalized_score": 60.0}, {"_id": {"$oid": "69d4eb12b877594bc571896f"}, "test_id": "T0190", "benchmark": "business_letters", "date": "2025-10-01", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-large-2411", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "mistral", "model": "mistral-large-latest", "duration": 3.137293577194214, "timestamp": "2025-10-01T15:42:36.181838", "text": "{\n \"metadata\": {\n \"send_date\": [\"1926-06-28\"],\n \"letter_title\": [null],\n \"sender_persons\": [\"Dr. Fritz Steiger\", \"Dr. Max Vischer\"],\n \"receiver_persons\": [\"P. Christ-Wackernagel\"]\n }\n}", "raw_response": {"id": "ca269025ea6e44d4b96d3e18618a9012", "model": "mistral-large-latest", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1926-06-28\"],\n \"letter_title\": [null],\n \"sender_persons\": [\"Dr. Fritz Steiger\", \"Dr. Max Vischer\"],\n \"receiver_persons\": [\"P. Christ-Wackernagel\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 2551, "completion_tokens": 73, "total_tokens": 2624}}, "usage": {"input_tokens": 2551, "output_tokens": 73, "total_tokens": 2624}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.46, "f1_micro": 0.43, "cost_summary": {"total_input_tokens": 80600, "total_output_tokens": 2433, "total_tokens": 83033, "input_cost_usd": 0.1612, "output_cost_usd": 0.014598, "total_cost_usd": 0.175798, "pricing_date": "2025-10-01", "input_price_per_million": 2.0, "output_price_per_million": 6.0}}, "normalized_score": 46.0}, {"_id": {"$oid": "69d4eb12b877594bc5718973"}, "test_id": "T0188", "benchmark": "business_letters", "date": "2025-10-01", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-large-2411", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "mistral", "model": "mistral-large-latest", "duration": 4.882924556732178, "timestamp": "2025-10-01T15:39:41.217685", "text": "{\n \"metadata\": {\n \"send_date\": [\"1928-04-23\"],\n \"letter_title\": [null],\n \"sender_persons\": [\"Rheinschiffahrt-Aktiengesellschaft\"],\n \"receiver_persons\": [\"Herrn Oettinger\"]\n }\n}", "raw_response": {"id": "2ed840e2aefc448689bf5efeb5e0bcbc", "model": "mistral-large-latest", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1928-04-23\"],\n \"letter_title\": [null],\n \"sender_persons\": [\"Rheinschiffahrt-Aktiengesellschaft\"],\n \"receiver_persons\": [\"Herrn Oettinger\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 1552, "completion_tokens": 68, "total_tokens": 1620}}, "usage": {"input_tokens": 1552, "output_tokens": 68, "total_tokens": 1620}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.42, "f1_micro": 0.45, "cost_summary": {"total_input_tokens": 129390, "total_output_tokens": 4239, "total_tokens": 133629, "input_cost_usd": 0.25878, "output_cost_usd": 0.025434, "total_cost_usd": 0.284214, "pricing_date": "2025-10-01", "input_price_per_million": 2.0, "output_price_per_million": 6.0}}, "normalized_score": 42.0}, {"_id": {"$oid": "69d4eb12b877594bc5718974"}, "test_id": "T0206", "benchmark": "business_letters", "date": "2025-10-01", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-flash-lite", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "genai", "model": "gemini-2.5-flash-lite", "duration": 0.678734540939331, "timestamp": "2025-10-01T00:23:48.914717", "text": "```json\n{\n \"letter_title\": [\n \"Basler Rheinschiffart-Aktiengesellschaft\"\n ],\n \"sender_persons\": [\n \"RHE INSCHIFFFAHRT-AKTIENGESELLSCHAFT\"\n ],\n \"send_date\": [\n \"1926-06-22\"\n ],\n \"receiver_persons\": [\n \"Herrn P. Christ - Wackernagel\"\n ]\n}\n```", "raw_response": {"text": "```json\n{\n \"letter_title\": [\n \"Basler Rheinschiffart-Aktiengesellschaft\"\n ],\n \"sender_persons\": [\n \"RHE INSCHIFFFAHRT-AKTIENGESELLSCHAFT\"\n ],\n \"send_date\": [\n \"1926-06-22\"\n ],\n \"receiver_persons\": [\n \"Herrn P. Christ - Wackernagel\"\n ]\n}\n```", "usage_metadata": {"prompt_token_count": 573, "candidates_token_count": 115, "total_token_count": 688}}, "usage": {"input_tokens": 573, "output_tokens": 115, "total_tokens": 688}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.49, "f1_micro": 0.44, "cost_summary": {"total_input_tokens": 26365, "total_output_tokens": 3530, "total_tokens": 29895, "input_cost_usd": 0.002636, "output_cost_usd": 0.001412, "total_cost_usd": 0.004049, "pricing_date": "2025-10-01", "input_price_per_million": 0.1, "output_price_per_million": 0.4}}, "normalized_score": 49.0}, {"_id": {"$oid": "69d4eb12b877594bc5718976"}, "test_id": "T0228", "benchmark": "business_letters", "date": "2025-10-01", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-sonnet-4-5-20250929", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "anthropic", "model": "claude-sonnet-4-5-20250929", "duration": 3.453526020050049, "timestamp": "2025-10-01T02:02:21.001517", "parsed": {"metadata": {"send_date": ["1932-12-19"], "letter_title": null, "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Dr. M. Vischer - von Planta"]}}, "text": "", "raw_response": {"id": "msg_01W85m9cex2proifF1MzZup2", "model": "claude-sonnet-4-5-20250929", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_018iGCYsgnrWVZ8sed7VZuz4", "name": "extract_structured_data", "input": {"metadata": {"letter_title": null, "send_date": ["1932-12-19"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Dr. M. Vischer - von Planta"]}}}], "stop_reason": "tool_use", "usage": {"input_tokens": 2177, "output_tokens": 105}}, "usage": {"input_tokens": 2177, "output_tokens": 105, "total_tokens": 2282}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.42, "f1_micro": 0.38, "cost_summary": {"total_input_tokens": 99579, "total_output_tokens": 3372, "total_tokens": 102951, "input_cost_usd": 0.298737, "output_cost_usd": 0.05058, "total_cost_usd": 0.349317, "pricing_date": "2025-10-01", "input_price_per_million": 3.0, "output_price_per_million": 15.0}}, "normalized_score": 42.0}, {"_id": {"$oid": "69d4eb12b877594bc571897c"}, "test_id": "T0173", "benchmark": "business_letters", "date": "2025-10-01", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-medium-2508", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "mistral", "model": "mistral-medium-2508", "duration": 1.430321216583252, "timestamp": "2025-10-01T14:06:01.367077", "text": "{\n \"metadata\": {\n \"send_date\": [\"1932-09-07\"],\n \"letter_title\": [\"Basler Rheinschiffahrtaktiengesellschaft\"],\n \"sender_persons\": [null],\n \"receiver_persons\": [null]\n }\n}", "raw_response": {"id": "0991f40cea6944a3bc16038742214476", "model": "mistral-medium-2508", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1932-09-07\"],\n \"letter_title\": [\"Basler Rheinschiffahrtaktiengesellschaft\"],\n \"sender_persons\": [null],\n \"receiver_persons\": [null]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 1552, "completion_tokens": 64, "total_tokens": 1616}}, "usage": {"input_tokens": 1552, "output_tokens": 64, "total_tokens": 1616}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.41, "f1_micro": 0.51, "cost_summary": {"total_input_tokens": 48790, "total_output_tokens": 1828, "total_tokens": 50618, "input_cost_usd": 0.019516, "output_cost_usd": 0.003656, "total_cost_usd": 0.023172, "pricing_date": "2025-10-01", "input_price_per_million": 0.4, "output_price_per_million": 2.0}}, "normalized_score": 41.0}, {"_id": {"$oid": "69d4eb12b877594bc5718982"}, "test_id": "T0175", "benchmark": "business_letters", "date": "2025-10-01", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-medium-2508", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "mistral", "model": "mistral-medium-2508", "duration": 3.1321239471435547, "timestamp": "2025-10-01T14:08:17.522304", "parsed": {"metadata": {"send_date": ["1928-04-26"], "letter_title": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Herrn Max Gettinger, Verkehrsbureau"]}}, "text": "", "raw_response": {"id": "405f7ccbf8784944b1310c1ad26d5514", "model": "mistral-medium-2508", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1928-04-26\"],\n \"letter_title\": [\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\n \"sender_persons\": [\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\n \"receiver_persons\": [\"Herrn Max Gettinger, Verkehrsbureau\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 1552, "completion_tokens": 84, "total_tokens": 1636}}, "usage": {"input_tokens": 1552, "output_tokens": 84, "total_tokens": 1636}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.45, "f1_micro": 0.42, "cost_summary": {"total_input_tokens": 80600, "total_output_tokens": 2428, "total_tokens": 83028, "input_cost_usd": 0.03224, "output_cost_usd": 0.004856, "total_cost_usd": 0.037096, "pricing_date": "2025-10-01", "input_price_per_million": 0.4, "output_price_per_million": 2.0}}, "normalized_score": 45.0}, {"_id": {"$oid": "69d4eb12b877594bc5718984"}, "test_id": "T0171", "benchmark": "business_letters", "date": "2025-10-01", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-medium-2508", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "mistral", "model": "mistral-medium-2508", "duration": 2.774606943130493, "timestamp": "2025-10-01T14:01:31.268702", "text": "{\n \"metadata\": {\n \"send_date\": [\"1929-05-27\"],\n \"letter_title\": [null],\n \"sender_persons\": [\"L\u00fctzelschwab\"],\n \"receiver_persons\": [\"Herrn\"]\n }\n}", "raw_response": {"id": "161944238e204a06a2a1c4befdeff364", "model": "mistral-medium-2508", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1929-05-27\"],\n \"letter_title\": [null],\n \"sender_persons\": [\"L\u00fctzelschwab\"],\n \"receiver_persons\": [\"Herrn\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 2551, "completion_tokens": 60, "total_tokens": 2611}}, "usage": {"input_tokens": 2551, "output_tokens": 60, "total_tokens": 2611}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.46, "f1_micro": 0.48, "cost_summary": {"total_input_tokens": 129390, "total_output_tokens": 4173, "total_tokens": 133563, "input_cost_usd": 0.051756, "output_cost_usd": 0.008346, "total_cost_usd": 0.060102, "pricing_date": "2025-10-01", "input_price_per_million": 0.4, "output_price_per_million": 2.0}}, "normalized_score": 46.0}, {"_id": {"$oid": "69d4eb12b877594bc5718986"}, "test_id": "T0226", "benchmark": "business_letters", "date": "2025-10-01", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-sonnet-4-5-20250929", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "anthropic", "model": "claude-sonnet-4-5-20250929", "duration": 3.388063669204712, "timestamp": "2025-10-01T01:54:36.004621", "parsed": {"metadata": {"send_date": ["1926-03-26"], "letter_title": null, "sender_persons": ["W. W. Mann"], "receiver_persons": ["Herrn Christ", "C/o. Paravicini, Christ & Co."]}}, "text": "", "raw_response": {"id": "msg_01PrfrPJ1fVgUqAZJXtLJshk", "model": "claude-sonnet-4-5-20250929", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01XYprFXkuixA74sF3vTp6Rw", "name": "extract_structured_data", "input": {"metadata": {"letter_title": null, "send_date": ["1926-03-26"], "sender_persons": ["W. W. Mann"], "receiver_persons": ["Herrn Christ", "C/o. Paravicini, Christ & Co."]}}}], "stop_reason": "tool_use", "usage": {"input_tokens": 2177, "output_tokens": 101}}, "usage": {"input_tokens": 2177, "output_tokens": 101, "total_tokens": 2278}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.43, "f1_micro": 0.44, "cost_summary": {"total_input_tokens": 163654, "total_output_tokens": 5834, "total_tokens": 169488, "input_cost_usd": 0.490962, "output_cost_usd": 0.08751, "total_cost_usd": 0.578472, "pricing_date": "2025-10-01", "input_price_per_million": 3.0, "output_price_per_million": 15.0}}, "normalized_score": 43.0}, {"_id": {"$oid": "69d4eb12b877594bc571898b"}, "test_id": "T0214", "benchmark": "business_letters", "date": "2025-10-01", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-flash-lite-preview-09-2025", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "genai", "model": "gemini-2.5-flash-lite-preview-09-2025", "duration": 0.7903316020965576, "timestamp": "2025-10-01T00:36:59.556850", "parsed": {"metadata": {"send_date": ["1932-09-07"], "letter_title": ["Betr. Personenschiffahrt"], "sender_persons": ["Basler Rheinschiffahrt Aktiengesellschaft"], "receiver_persons": ["Herr Dr. M.Vischer-von Planta"]}}, "text": "{\n \"metadata\": {\n \"send_date\": [\n \"1932-09-07\"\n ],\n \"letter_title\": [\n \"Betr. Personenschiffahrt\"\n ],\n \"sender_persons\": [\n \"Basler Rheinschiffahrt Aktiengesellschaft\"\n ],\n \"receiver_persons\": [\n \"Herr Dr. M.Vischer-von Planta\"\n ]\n }\n}", "raw_response": {"text": "{\n \"metadata\": {\n \"send_date\": [\n \"1932-09-07\"\n ],\n \"letter_title\": [\n \"Betr. Personenschiffahrt\"\n ],\n \"sender_persons\": [\n \"Basler Rheinschiffahrt Aktiengesellschaft\"\n ],\n \"receiver_persons\": [\n \"Herr Dr. M.Vischer-von Planta\"\n ]\n }\n}", "usage_metadata": {"prompt_token_count": 1091, "candidates_token_count": 108, "total_token_count": 1203}}, "usage": {"input_tokens": 1091, "output_tokens": 108, "total_tokens": 1203}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.53, "f1_micro": 0.48, "cost_summary": {"total_input_tokens": 26365, "total_output_tokens": 3290, "total_tokens": 29655, "input_cost_usd": 0.002636, "output_cost_usd": 0.001316, "total_cost_usd": 0.003953, "pricing_date": "2025-10-01", "input_price_per_million": 0.1, "output_price_per_million": 0.4}}, "normalized_score": 53.0}, {"_id": {"$oid": "69d4eb12b877594bc571898f"}, "test_id": "T0227", "benchmark": "business_letters", "date": "2025-10-01", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-sonnet-4-5-20250929", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "anthropic", "model": "claude-sonnet-4-5-20250929", "duration": 3.228788137435913, "timestamp": "2025-10-01T02:00:12.253553", "parsed": {"metadata": {"send_date": ["1922-08-15"], "letter_title": null, "sender_persons": ["Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["Basler Rheinschiffahrts A.-G."]}}, "text": "", "raw_response": {"id": "msg_015WjTkUrfAqyrtxhwcejjEA", "model": "claude-sonnet-4-5-20250929", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01LGC54MautWcE6snknTXGuo", "name": "extract_structured_data", "input": {"metadata": {"letter_title": null, "send_date": ["1922-08-15"], "sender_persons": ["Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["Basler Rheinschiffahrts A.-G."]}}}], "stop_reason": "tool_use", "usage": {"input_tokens": 2177, "output_tokens": 104}}, "usage": {"input_tokens": 2177, "output_tokens": 104, "total_tokens": 2281}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.39, "f1_micro": 0.44, "cost_summary": {"total_input_tokens": 64075, "total_output_tokens": 2465, "total_tokens": 66540, "input_cost_usd": 0.192225, "output_cost_usd": 0.036975, "total_cost_usd": 0.2292, "pricing_date": "2025-10-01", "input_price_per_million": 3.0, "output_price_per_million": 15.0}}, "normalized_score": 39.0}, {"_id": {"$oid": "69d4eb12b877594bc5718991"}, "test_id": "T0136", "benchmark": "business_letters", "date": "2025-10-01", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "o3", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "o3", "duration": 19.05803871154785, "timestamp": "2025-10-01T00:32:44.062447", "parsed": {"metadata": {"send_date": ["1928-03-01"], "letter_title": ["Betrifft Ihr Schreiben vom 27. Februar."], "sender_persons": null, "receiver_persons": null}}, "text": "", "raw_response": {"id": "chatcmpl-CLdBSiBQ08oXno9pIUDxGyHsrz0bk", "model": "o3-2025-04-16", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\"metadata\":{\"send_date\":[\"1928-03-01\"],\"letter_title\":[\"Betrifft Ihr Schreiben vom 27. Februar.\"],\"sender_persons\":null,\"receiver_persons\":null}}", "role": "assistant"}}], "usage": {"prompt_tokens": 1838, "completion_tokens": 638, "total_tokens": 2476}}, "usage": {"input_tokens": 1838, "output_tokens": 638, "total_tokens": 2476}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.61, "f1_micro": 0.6, "cost_summary": {"total_input_tokens": 58141, "total_output_tokens": 23617, "total_tokens": 81758, "input_cost_usd": 0.116282, "output_cost_usd": 0.188936, "total_cost_usd": 0.305218, "pricing_date": "2025-10-01", "input_price_per_million": 2.0, "output_price_per_million": 8.0}}, "normalized_score": 61.0}, {"_id": {"$oid": "69d4eb12b877594bc5718993"}, "test_id": "T0176", "benchmark": "business_letters", "date": "2025-10-01", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-medium-2505", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "mistral", "model": "mistral-medium-2505", "duration": 2.0799219608306885, "timestamp": "2025-10-01T14:11:06.180524", "parsed": {"metadata": {"send_date": ["1935-08-16"], "letter_title": ["Basler Rheinschiffahrt Aktiengesellschaft"], "sender_persons": ["Basler Personenschiffahrt-Gesellschaft"], "receiver_persons": null}}, "text": "", "raw_response": {"id": "a97e381960f64c6b84875a49e75159ec", "model": "mistral-medium-2505", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1935-08-16\"],\n \"letter_title\": [\"Basler Rheinschiffahrt Aktiengesellschaft\"],\n \"sender_persons\": [\"Basler Personenschiffahrt-Gesellschaft\"],\n \"receiver_persons\": null\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 1552, "completion_tokens": 69, "total_tokens": 1621}}, "usage": {"input_tokens": 1552, "output_tokens": 69, "total_tokens": 1621}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.46, "f1_micro": 0.43, "cost_summary": {"total_input_tokens": 80600, "total_output_tokens": 2437, "total_tokens": 83037, "input_cost_usd": 0.03224, "output_cost_usd": 0.004874, "total_cost_usd": 0.037114, "pricing_date": "2025-10-01", "input_price_per_million": 0.4, "output_price_per_million": 2.0}}, "normalized_score": 46.0}, {"_id": {"$oid": "69d4eb12b877594bc5718997"}, "test_id": "T0174", "benchmark": "business_letters", "date": "2025-10-01", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-medium-2505", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "mistral", "model": "mistral-medium-2505", "duration": 1.6262760162353516, "timestamp": "2025-10-01T14:06:27.773423", "text": "{\n \"metadata\": {\n \"send_date\": [\"1926-07-13\"],\n \"letter_title\": [null],\n \"sender_persons\": [\"Einer Personenschiffahrtsgesellschaft\"],\n \"receiver_persons\": [\"ALBATROS\"]\n }\n}", "raw_response": {"id": "d285ce91e23a4d3a8c3fdd0a673eb9bf", "model": "mistral-medium-2505", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1926-07-13\"],\n \"letter_title\": [null],\n \"sender_persons\": [\"Einer Personenschiffahrtsgesellschaft\"],\n \"receiver_persons\": [\"ALBATROS\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 1552, "completion_tokens": 65, "total_tokens": 1617}}, "usage": {"input_tokens": 1552, "output_tokens": 65, "total_tokens": 1617}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.47, "f1_micro": 0.59, "cost_summary": {"total_input_tokens": 48790, "total_output_tokens": 1813, "total_tokens": 50603, "input_cost_usd": 0.019516, "output_cost_usd": 0.003626, "total_cost_usd": 0.023142, "pricing_date": "2025-10-01", "input_price_per_million": 0.4, "output_price_per_million": 2.0}}, "normalized_score": 47.0}, {"_id": {"$oid": "69d4eb12b877594bc571899b"}, "test_id": "T0204", "benchmark": "business_letters", "date": "2025-10-01", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-flash-lite", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "genai", "model": "gemini-2.5-flash-lite", "duration": 0.7229833602905273, "timestamp": "2025-10-01T00:23:12.775500", "parsed": {"metadata": {"send_date": ["1935-08-16"], "letter_title": ["BASLER RHEINSCHIFFFAHRT AKTIENGESELLSCHAFT"], "sender_persons": ["BASLER RHEINSCHIFFFAHRT AKTIENGESELLSCHAFT"], "receiver_persons": ["Basler Personenschiffahrts-Gesellschaft, Basel"]}}, "text": "{\n \"metadata\": {\n \"send_date\": [\n \"1935-08-16\"\n ],\n \"letter_title\": [\n \"BASLER RHEINSCHIFFFAHRT AKTIENGESELLSCHAFT\"\n ],\n \"sender_persons\": [\n \"BASLER RHEINSCHIFFFAHRT AKTIENGESELLSCHAFT\"\n ],\n \"receiver_persons\": [\n \"Basler Personenschiffahrts-Gesellschaft, Basel\"\n ]\n }\n}", "raw_response": {"text": "{\n \"metadata\": {\n \"send_date\": [\n \"1935-08-16\"\n ],\n \"letter_title\": [\n \"BASLER RHEINSCHIFFFAHRT AKTIENGESELLSCHAFT\"\n ],\n \"sender_persons\": [\n \"BASLER RHEINSCHIFFFAHRT AKTIENGESELLSCHAFT\"\n ],\n \"receiver_persons\": [\n \"Basler Personenschiffahrts-Gesellschaft, Basel\"\n ]\n }\n}", "usage_metadata": {"prompt_token_count": 573, "candidates_token_count": 129, "total_token_count": 702}}, "usage": {"input_tokens": 573, "output_tokens": 129, "total_tokens": 702}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.46, "f1_micro": 0.46, "cost_summary": {"total_input_tokens": 43280, "total_output_tokens": 6297, "total_tokens": 49577, "input_cost_usd": 0.004328, "output_cost_usd": 0.002519, "total_cost_usd": 0.006847, "pricing_date": "2025-10-01", "input_price_per_million": 0.1, "output_price_per_million": 0.4}}, "normalized_score": 46.0}, {"_id": {"$oid": "69d4eb12b877594bc5718950"}, "test_id": "T0205", "benchmark": "business_letters", "date": "2025-10-01", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-flash-lite", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "genai", "model": "gemini-2.5-flash-lite", "duration": 1.2504346370697021, "timestamp": "2025-10-01T00:23:29.198890", "parsed": {"metadata": {"send_date": ["1928-04-23"], "letter_title": ["Kaufvertrag"], "sender_persons": ["Basler Rheinschifffahrt-Aktiengesellschaft"], "receiver_persons": ["Basler Personenschifffahrt"]}}, "text": "{\n \"metadata\": {\n \"send_date\": [\n \"1928-04-23\"\n ],\n \"letter_title\": [\n \"Kaufvertrag\"\n ],\n \"sender_persons\": [\n \"Basler Rheinschifffahrt-Aktiengesellschaft\"\n ],\n \"receiver_persons\": [\n \"Basler Personenschifffahrt\"\n ]\n }\n}", "raw_response": {"text": "{\n \"metadata\": {\n \"send_date\": [\n \"1928-04-23\"\n ],\n \"letter_title\": [\n \"Kaufvertrag\"\n ],\n \"sender_persons\": [\n \"Basler Rheinschifffahrt-Aktiengesellschaft\"\n ],\n \"receiver_persons\": [\n \"Basler Personenschifffahrt\"\n ]\n }\n}", "usage_metadata": {"prompt_token_count": 832, "candidates_token_count": 103, "total_token_count": 935}}, "usage": {"input_tokens": 832, "output_tokens": 103, "total_tokens": 935}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.44, "f1_micro": 0.51, "cost_summary": {"total_input_tokens": 16915, "total_output_tokens": 2733, "total_tokens": 19648, "input_cost_usd": 0.001692, "output_cost_usd": 0.001093, "total_cost_usd": 0.002785, "pricing_date": "2025-10-01", "input_price_per_million": 0.1, "output_price_per_million": 0.4}}, "normalized_score": 44.0}, {"_id": {"$oid": "69d4eb12b877594bc5718955"}, "test_id": "T0212", "benchmark": "business_letters", "date": "2025-10-01", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-flash-lite-preview-09-2025", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "genai", "model": "gemini-2.5-flash-lite-preview-09-2025", "duration": 0.59187912940979, "timestamp": "2025-10-01T00:35:22.374171", "parsed": {"metadata": {"send_date": ["1926-07-13"], "letter_title": ["Betr. \"ALBATROS\"."], "sender_persons": ["Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["Elektrizit\u00e4tswerk, Basel"]}}, "text": "{\n \"metadata\": {\n \"send_date\": [\n \"1926-07-13\"\n ],\n \"letter_title\": [\n \"Betr. \\\"ALBATROS\\\".\"\n ],\n \"sender_persons\": [\n \"Basler Personenschiffahrtsgesellschaft\"\n ],\n \"receiver_persons\": [\n \"Elektrizit\u00e4tswerk, Basel\"\n ]\n }\n}", "raw_response": {"text": "{\n \"metadata\": {\n \"send_date\": [\n \"1926-07-13\"\n ],\n \"letter_title\": [\n \"Betr. \\\"ALBATROS\\\".\"\n ],\n \"sender_persons\": [\n \"Basler Personenschiffahrtsgesellschaft\"\n ],\n \"receiver_persons\": [\n \"Elektrizit\u00e4tswerk, Basel\"\n ]\n }\n}", "usage_metadata": {"prompt_token_count": 573, "candidates_token_count": 104, "total_token_count": 681}}, "usage": {"input_tokens": 573, "output_tokens": 104, "total_tokens": 681}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.5, "f1_micro": 0.5, "cost_summary": {"total_input_tokens": 43280, "total_output_tokens": 5634, "total_tokens": 48914, "input_cost_usd": 0.004328, "output_cost_usd": 0.002254, "total_cost_usd": 0.006582, "pricing_date": "2025-10-01", "input_price_per_million": 0.1, "output_price_per_million": 0.4}}, "normalized_score": 50.0}, {"_id": {"$oid": "69d4eb12b877594bc5718958"}, "test_id": "T0135", "benchmark": "business_letters", "date": "2025-10-01", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "o3", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "o3", "duration": 7.69835352897644, "timestamp": "2025-10-01T00:23:06.461284", "parsed": {"metadata": {"send_date": ["1926-03-29"], "letter_title": null, "sender_persons": null, "receiver_persons": ["Dr. W. Krasting"]}}, "text": "", "raw_response": {"id": "chatcmpl-CLd2JE5EC6ug7KMMuvlotlQA311Mn", "model": "o3-2025-04-16", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\"metadata\":{\"send_date\":[\"1926-03-29\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":[\"Dr. W. Krasting\"]}}", "role": "assistant"}}], "usage": {"prompt_tokens": 1163, "completion_tokens": 250, "total_tokens": 1413}}, "usage": {"input_tokens": 1163, "output_tokens": 250, "total_tokens": 1413}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.61, "f1_micro": 0.73, "cost_summary": {"total_input_tokens": 35825, "total_output_tokens": 14232, "total_tokens": 50057, "input_cost_usd": 0.07165, "output_cost_usd": 0.113856, "total_cost_usd": 0.185506, "pricing_date": "2025-10-01", "input_price_per_million": 2.0, "output_price_per_million": 8.0}}, "normalized_score": 61.0}, {"_id": {"$oid": "69d4eb12b877594bc571895b"}, "test_id": "T0172", "benchmark": "business_letters", "date": "2025-10-01", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-medium-2505", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "mistral", "model": "mistral-medium-2505", "duration": 2.834023952484131, "timestamp": "2025-10-01T14:02:52.490448", "parsed": {"metadata": {"send_date": ["1926-08-13"], "letter_title": ["AB SCHRIFT"], "sender_persons": ["Rheinischaft-Aktiengesellschaft"], "receiver_persons": ["Herrn Dr. Max Vischer"]}}, "text": "", "raw_response": {"id": "9658ac4d672749cfb09a17d218c8cb79", "model": "mistral-medium-2505", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1926-08-13\"],\n \"letter_title\": [\"AB SCHRIFT\"],\n \"sender_persons\": [\"Rheinischaft-Aktiengesellschaft\"],\n \"receiver_persons\": [\"Herrn Dr. Max Vischer\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 3550, "completion_tokens": 72, "total_tokens": 3622}}, "usage": {"input_tokens": 3550, "output_tokens": 72, "total_tokens": 3622}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.45, "f1_micro": 0.47, "cost_summary": {"total_input_tokens": 129390, "total_output_tokens": 4242, "total_tokens": 133632, "input_cost_usd": 0.051756, "output_cost_usd": 0.008484, "total_cost_usd": 0.06024, "pricing_date": "2025-10-01", "input_price_per_million": 0.4, "output_price_per_million": 2.0}}, "normalized_score": 45.0}, {"_id": {"$oid": "69d4eb12b877594bc571895c"}, "test_id": "T0213", "benchmark": "business_letters", "date": "2025-10-01", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-flash-lite-preview-09-2025", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "genai", "model": "gemini-2.5-flash-lite-preview-09-2025", "duration": 0.7119410037994385, "timestamp": "2025-10-01T00:36:09.481778", "parsed": {"metadata": {"send_date": ["1926-03-29"], "letter_title": ["Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926"], "sender_persons": ["null"], "receiver_persons": ["Dr.W.Krasting"]}}, "text": "{\n \"metadata\": {\n \"send_date\": [\n \"1926-03-29\"\n ],\n \"letter_title\": [\n \"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\"\n ],\n \"sender_persons\": [\n \"null\"\n ],\n \"receiver_persons\": [\n \"Dr.W.Krasting\"\n ]\n }\n}", "raw_response": {"text": "{\n \"metadata\": {\n \"send_date\": [\n \"1926-03-29\"\n ],\n \"letter_title\": [\n \"Internationale Ausstellung f\u00fcr Binnenschiffahrt und Wasserkraftnutzung Basel 1926\"\n ],\n \"sender_persons\": [\n \"null\"\n ],\n \"receiver_persons\": [\n \"Dr.W.Krasting\"\n ]\n }\n}", "usage_metadata": {"prompt_token_count": 573, "candidates_token_count": 110, "total_token_count": 687}}, "usage": {"input_tokens": 573, "output_tokens": 110, "total_tokens": 687}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.45, "f1_micro": 0.55, "cost_summary": {"total_input_tokens": 16915, "total_output_tokens": 2348, "total_tokens": 19263, "input_cost_usd": 0.001692, "output_cost_usd": 0.000939, "total_cost_usd": 0.002631, "pricing_date": "2025-10-01", "input_price_per_million": 0.1, "output_price_per_million": 0.4}}, "normalized_score": 45.0}, {"_id": {"$oid": "69d4eb12b877594bc571896a"}, "test_id": "T0189", "benchmark": "business_letters", "date": "2025-10-01", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "mistral-large-2411", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "mistral", "model": "mistral-large-latest", "duration": 2.6110360622406006, "timestamp": "2025-10-01T15:42:07.220871", "text": "{\n \"metadata\": {\n \"send_date\": [\"1932-12-21\"],\n \"letter_title\": [\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\n \"sender_persons\": [null],\n \"receiver_persons\": [\"Basler Personenschiffahrtsgesellschaft\"]\n }\n}", "raw_response": {"id": "dd65f91e420c434cb16e82e4b6b3d74f", "model": "mistral-large-latest", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1932-12-21\"],\n \"letter_title\": [\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\n \"sender_persons\": [null],\n \"receiver_persons\": [\"Basler Personenschiffahrtsgesellschaft\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 1552, "completion_tokens": 72, "total_tokens": 1624}}, "usage": {"input_tokens": 1552, "output_tokens": 72, "total_tokens": 1624}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.42, "f1_micro": 0.54, "cost_summary": {"total_input_tokens": 48790, "total_output_tokens": 1772, "total_tokens": 50562, "input_cost_usd": 0.09758, "output_cost_usd": 0.010632, "total_cost_usd": 0.108212, "pricing_date": "2025-10-01", "input_price_per_million": 2.0, "output_price_per_million": 6.0}}, "normalized_score": 42.0}, {"_id": {"$oid": "69d4eb12b877594bc57188e2"}, "test_id": "T0045", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.0-flash", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "genai", "model": "gemini-2.0-flash", "duration": 2.3527286052703857, "timestamp": "2025-09-30T15:16:03.555381", "parsed": {"metadata": {"send_date": ["1928-04-02"], "letter_title": ["null"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Basler Personenschiffahrtsgesellschaft", "Kur- und Verkehrsverein"]}}, "text": "{\n \"metadata\": {\n \"send_date\": [\"1928-04-02\"],\n \"letter_title\": [\"null\"],\n \"sender_persons\": [\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\n \"receiver_persons\": [\"Basler Personenschiffahrtsgesellschaft\", \"Kur- und Verkehrsverein\"]\n }\n}", "raw_response": {"text": "{\n \"metadata\": {\n \"send_date\": [\"1928-04-02\"],\n \"letter_title\": [\"null\"],\n \"sender_persons\": [\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\n \"receiver_persons\": [\"Basler Personenschiffahrtsgesellschaft\", \"Kur- und Verkehrsverein\"]\n }\n}", "usage_metadata": {"prompt_token_count": 1394, "candidates_token_count": 84, "total_token_count": 1478}}, "usage": {"input_tokens": 1394, "output_tokens": 84, "total_tokens": 1478}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.54, "f1_micro": 0.48, "cost_summary": {"total_input_tokens": 51058, "total_output_tokens": 3002, "total_tokens": 54060, "input_cost_usd": 0.005106, "output_cost_usd": 0.001201, "total_cost_usd": 0.006307, "pricing_date": "2025-09-30", "input_price_per_million": 0.1, "output_price_per_million": 0.4}}, "normalized_score": 54.0}, {"_id": {"$oid": "69d4eb12b877594bc57188e3"}, "test_id": "T0071", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4.1-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-4.1-mini", "duration": 1.4035866260528564, "timestamp": "2025-09-30T18:01:53.790434", "parsed": {"metadata": {"send_date": ["1928-05-15"], "letter_title": ["ABSCHRIFT"], "sender_persons": ["null"], "receiver_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"]}}, "text": "", "raw_response": {"id": "chatcmpl-CLX5O9gKTJIwNOfOWQzPJxJ1XFS9L", "model": "gpt-4.1-mini-2025-04-14", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\"metadata\":{\"send_date\":[\"1928-05-15\"],\"letter_title\":[\"ABSCHRIFT\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"]}}", "role": "assistant"}}], "usage": {"prompt_tokens": 1686, "completion_tokens": 46, "total_tokens": 1732}}, "usage": {"input_tokens": 1686, "output_tokens": 46, "total_tokens": 1732}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.42, "f1_micro": 0.54, "cost_summary": {"total_input_tokens": 54090, "total_output_tokens": 1331, "total_tokens": 55421, "input_cost_usd": 0.021636, "output_cost_usd": 0.00213, "total_cost_usd": 0.023766, "pricing_date": "2025-09-30", "input_price_per_million": 0.4, "output_price_per_million": 1.6}}, "normalized_score": 42.0}, {"_id": {"$oid": "69d4eb12b877594bc57188e4"}, "test_id": "T0196", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-flash", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "genai", "model": "gemini-2.5-flash", "duration": 6.71971869468689, "timestamp": "2025-09-30T23:16:22.749357", "parsed": {"metadata": {"send_date": ["1928-05-15"], "letter_title": null, "sender_persons": null, "receiver_persons": ["Basler Rheinschifffahrt - Aktiengesellschaft"]}}, "text": "{\"metadata\": {\"send_date\": [\"1928-05-15\"], \"letter_title\": null, \"sender_persons\": null, \"receiver_persons\": [\"Basler Rheinschifffahrt - Aktiengesellschaft\"]}}", "raw_response": {"text": "{\"metadata\": {\"send_date\": [\"1928-05-15\"], \"letter_title\": null, \"sender_persons\": null, \"receiver_persons\": [\"Basler Rheinschifffahrt - Aktiengesellschaft\"]}}", "usage_metadata": {"prompt_token_count": 573, "candidates_token_count": 53, "total_token_count": 1510}}, "usage": {"input_tokens": 573, "output_tokens": 53, "total_tokens": 1510}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.53, "f1_micro": 0.54, "cost_summary": {"total_input_tokens": 43280, "total_output_tokens": 3502, "total_tokens": 46782, "input_cost_usd": 0.012984, "output_cost_usd": 0.008755, "total_cost_usd": 0.021739, "pricing_date": "2025-09-30", "input_price_per_million": 0.3, "output_price_per_million": 2.5}}, "normalized_score": 53.0}, {"_id": {"$oid": "69d4eb12b877594bc57188e5"}, "test_id": "T0198", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-flash", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "genai", "model": "gemini-2.5-flash", "duration": 4.205246210098267, "timestamp": "2025-09-30T23:22:47.765953", "parsed": {"metadata": {"send_date": ["1936-06-28"], "letter_title": null, "sender_persons": ["Max Vischer"], "receiver_persons": ["P. Christ-Wackernagel"]}}, "text": "{\"metadata\": {\"send_date\": [\"1936-06-28\"], \"letter_title\": null, \"sender_persons\": [\"Max Vischer\"], \"receiver_persons\": [\"P. Christ-Wackernagel\"]}}", "raw_response": {"text": "{\"metadata\": {\"send_date\": [\"1936-06-28\"], \"letter_title\": null, \"sender_persons\": [\"Max Vischer\"], \"receiver_persons\": [\"P. Christ-Wackernagel\"]}}", "usage_metadata": {"prompt_token_count": 832, "candidates_token_count": 53, "total_token_count": 1277}}, "usage": {"input_tokens": 832, "output_tokens": 53, "total_tokens": 1277}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.57, "f1_micro": 0.52, "cost_summary": {"total_input_tokens": 26365, "total_output_tokens": 2035, "total_tokens": 28400, "input_cost_usd": 0.007909, "output_cost_usd": 0.005088, "total_cost_usd": 0.012997, "pricing_date": "2025-09-30", "input_price_per_million": 0.3, "output_price_per_million": 2.5}}, "normalized_score": 56.99999999999999}, {"_id": {"$oid": "69d4eb12b877594bc57188e6"}, "test_id": "T0067", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4.1", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-4.1", "duration": 10.795608043670654, "timestamp": "2025-09-30T17:51:56.711655", "parsed": {"metadata": {"send_date": ["1928-04-02"], "letter_title": ["Betrifft Schifffahrt Basel-Rheinfelden"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Basler Personenschiffahrtsgesellschaft", "Kur- und Verkehrsverein Rheinfelden"]}}, "text": "", "raw_response": {"id": "chatcmpl-CLWvgCG0sz6aklI0tv2xhn4yOLawt", "model": "gpt-4.1-2025-04-14", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1928-04-02\"],\n \"letter_title\": [\"Betrifft Schifffahrt Basel-Rheinfelden\"],\n \"sender_persons\": [\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\n \"receiver_persons\": [\"Basler Personenschiffahrtsgesellschaft\", \"Kur- und Verkehrsverein Rheinfelden\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 3552, "completion_tokens": 86, "total_tokens": 3638}}, "usage": {"input_tokens": 3552, "output_tokens": 86, "total_tokens": 3638}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.51, "f1_micro": 0.51, "cost_summary": {"total_input_tokens": 103014, "total_output_tokens": 3590, "total_tokens": 106604, "input_cost_usd": 0.206028, "output_cost_usd": 0.02872, "total_cost_usd": 0.234748, "pricing_date": "2025-09-30", "input_price_per_million": 2.0, "output_price_per_million": 8.0}}, "normalized_score": 51.0}, {"_id": {"$oid": "69d4eb12b877594bc57188e8"}, "test_id": "T0060", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "pixtral-large-2411", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "mistral", "model": "pixtral-large-latest", "duration": 1.9495394229888916, "timestamp": "2025-09-30T15:22:36.755360", "text": "{\n \"letter_title\": [\"null\"],\n \"send_date\": [\"1968-02-23\"],\n \"sender_persons\": [\"Der Pr\u00e4sident\"],\n \"receiver_persons\": [\"Basler Rheinschiffahrts A.-G.\", \"Basel\", \"Marktgasse 5\"]\n}", "raw_response": {"id": "31dd5e1e161f45f6a21a5032989abf8f", "model": "pixtral-large-latest", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"letter_title\": [\"null\"],\n \"send_date\": [\"1968-02-23\"],\n \"sender_persons\": [\"Der Pr\u00e4sident\"],\n \"receiver_persons\": [\"Basler Rheinschiffahrts A.-G.\", \"Basel\", \"Marktgasse 5\"]\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 3614, "completion_tokens": 79, "total_tokens": 3693}}, "usage": {"input_tokens": 3614, "output_tokens": 79, "total_tokens": 3693}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.27, "f1_micro": 0.31, "cost_summary": {"total_input_tokens": 120430, "total_output_tokens": 2267, "total_tokens": 122697, "input_cost_usd": 0.24086, "output_cost_usd": 0.013602, "total_cost_usd": 0.254462, "pricing_date": "2025-09-30", "input_price_per_million": 2.0, "output_price_per_million": 6.0}}, "normalized_score": 27.0}, {"_id": {"$oid": "69d4eb12b877594bc57188e9"}, "test_id": "T0114", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5-nano", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-5-nano", "duration": 18.485656261444092, "timestamp": "2025-09-30T22:09:44.297403", "parsed": {"metadata": {"send_date": ["1926-06-22"], "letter_title": ["null"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["P. Christ-Wackernagel"]}}, "text": "", "raw_response": {"id": "chatcmpl-CLax41gWgfd70vKoIL8FsoNamzenK", "model": "gpt-5-nano-2025-08-07", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1926-06-22\"],\n \"letter_title\": [\"null\"],\n \"sender_persons\": [\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\n \"receiver_persons\": [\"P. Christ-Wackernagel\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 1593, "completion_tokens": 1932, "total_tokens": 3525}}, "usage": {"input_tokens": 1593, "output_tokens": 1932, "total_tokens": 3525}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.43, "f1_micro": 0.46, "cost_summary": {"total_input_tokens": 136106, "total_output_tokens": 145909, "total_tokens": 282015, "input_cost_usd": 0.006805, "output_cost_usd": 0.058364, "total_cost_usd": 0.065169, "pricing_date": "2025-09-30", "input_price_per_million": 0.05, "output_price_per_million": 0.4}}, "normalized_score": 43.0}, {"_id": {"$oid": "69d4eb12b877594bc57188ea"}, "test_id": "T0116", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5-nano", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-5-nano", "duration": 15.864559173583984, "timestamp": "2025-09-30T22:33:44.979822", "parsed": {"metadata": {"send_date": ["1928-03-22"], "letter_title": ["null"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Vorstand der Basler Personenschifffahrtgesellschaft, Basel"]}}, "text": "", "raw_response": {"id": "chatcmpl-CLbKMhN8MKyZPSG1iQ2Kp2EQMH15Y", "model": "gpt-5-nano-2025-08-07", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1928-03-22\"],\n \"letter_title\": [\"null\"],\n \"sender_persons\": [\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\n \"receiver_persons\": [\"Vorstand der Basler Personenschifffahrtgesellschaft, Basel\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 4908, "completion_tokens": 3412, "total_tokens": 8320}}, "usage": {"input_tokens": 4908, "output_tokens": 3412, "total_tokens": 8320}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.51, "f1_micro": 0.46, "cost_summary": {"total_input_tokens": 85231, "total_output_tokens": 74571, "total_tokens": 159802, "input_cost_usd": 0.004262, "output_cost_usd": 0.029828, "total_cost_usd": 0.03409, "pricing_date": "2025-09-30", "input_price_per_million": 0.05, "output_price_per_million": 0.4}}, "normalized_score": 51.0}, {"_id": {"$oid": "69d4eb12b877594bc57188ed"}, "test_id": "T0111", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-5-mini", "duration": 18.99602723121643, "timestamp": "2025-09-30T21:40:09.516180", "parsed": {"metadata": {"send_date": ["1928-04-02"], "letter_title": ["Betrifft Schifffahrt Basel-Rheinfelden"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Basler Personenschiffahrtsgesellschaft (Basel)", "Kur- und Verkehrsverein, Rheinfelden"]}}, "text": "", "raw_response": {"id": "chatcmpl-CLaURMfYkLc7udtVibUSq0d4iinlO", "model": "gpt-5-mini-2025-08-07", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\"metadata\":{\"send_date\":[\"1928-04-02\"],\"letter_title\":[\"Betrifft Schifffahrt Basel-Rheinfelden\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Basler Personenschiffahrtsgesellschaft (Basel)\",\"Kur- und Verkehrsverein, Rheinfelden\"]}}", "role": "assistant"}}], "usage": {"prompt_tokens": 4028, "completion_tokens": 1240, "total_tokens": 5268}}, "usage": {"input_tokens": 4028, "output_tokens": 1240, "total_tokens": 5268}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.53, "f1_micro": 0.54, "cost_summary": {"total_input_tokens": 114546, "total_output_tokens": 59989, "total_tokens": 174535, "input_cost_usd": 0.028636, "output_cost_usd": 0.119978, "total_cost_usd": 0.148615, "pricing_date": "2025-09-30", "input_price_per_million": 0.25, "output_price_per_million": 2.0}}, "normalized_score": 53.0}, {"_id": {"$oid": "69d4eb12b877594bc57188f0"}, "test_id": "T0042", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4o-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-4o-mini", "duration": 3.3004214763641357, "timestamp": "2025-09-30T15:12:35.360986", "parsed": {"metadata": {"send_date": ["1935-08-17"], "letter_title": ["Letter from Basler Personenschifffahrtsgesellschaft"], "sender_persons": ["Basler Personenschifffahrtsgesellschaft"], "receiver_persons": ["Herr Fritz Ritter", "Basler Rheinschiffahrt A.-G."]}}, "text": "", "raw_response": {"id": "chatcmpl-CLURWmpznPNEKJmnTEYGEIjiWTxUq", "model": "gpt-4o-mini-2024-07-18", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1935-08-17\"],\n \"letter_title\": [\"Letter from Basler Personenschifffahrtsgesellschaft\"],\n \"sender_persons\": [\"Basler Personenschifffahrtsgesellschaft\"],\n \"receiver_persons\": [\"Herr Fritz Ritter\", \"Basler Rheinschiffahrt A.-G.\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 25993, "completion_tokens": 80, "total_tokens": 26073}}, "usage": {"input_tokens": 25993, "output_tokens": 80, "total_tokens": 26073}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.44, "f1_micro": 0.53, "cost_summary": {"total_input_tokens": 904835, "total_output_tokens": 1719, "total_tokens": 906554, "input_cost_usd": 0.135725, "output_cost_usd": 0.001031, "total_cost_usd": 0.136757, "pricing_date": "2025-09-30", "input_price_per_million": 0.15, "output_price_per_million": 0.6}}, "normalized_score": 44.0}, {"_id": {"$oid": "69d4eb12b877594bc57188f1"}, "test_id": "T0056", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.0-flash-lite", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "genai", "model": "gemini-2.0-flash-lite", "duration": 2.384533643722534, "timestamp": "2025-09-30T15:20:36.219102", "parsed": {"metadata": {"send_date": ["1926-06-26"], "letter_title": ["null"], "sender_persons": ["Basler Personenschifffahrtsgesellschaft"], "receiver_persons": ["Direktion der Basler Rheinschifffahrt Aktiengesellschaft", "Herrn O. Ritter"]}}, "text": "{\n \"metadata\": {\n \"send_date\": [\n \"1926-06-26\"\n ],\n \"letter_title\": [\n \"null\"\n ],\n \"sender_persons\": [\n \"Basler Personenschifffahrtsgesellschaft\"\n ],\n \"receiver_persons\": [\n \"Direktion der Basler Rheinschifffahrt Aktiengesellschaft\",\n \"Herrn O. Ritter\"\n ]\n }\n}", "raw_response": {"text": "{\n \"metadata\": {\n \"send_date\": [\n \"1926-06-26\"\n ],\n \"letter_title\": [\n \"null\"\n ],\n \"sender_persons\": [\n \"Basler Personenschifffahrtsgesellschaft\"\n ],\n \"receiver_persons\": [\n \"Direktion der Basler Rheinschifffahrt Aktiengesellschaft\",\n \"Herrn O. Ritter\"\n ]\n }\n}", "usage_metadata": {"prompt_token_count": 1394, "candidates_token_count": 114, "total_token_count": 1508}}, "usage": {"input_tokens": 1394, "output_tokens": 114, "total_tokens": 1508}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.51, "f1_micro": 0.63, "cost_summary": {"total_input_tokens": 45944, "total_output_tokens": 2386, "total_tokens": 48330, "input_cost_usd": 0.003446, "output_cost_usd": 0.000716, "total_cost_usd": 0.004162, "pricing_date": "2025-09-30", "input_price_per_million": 0.075, "output_price_per_million": 0.3}}, "normalized_score": 51.0}, {"_id": {"$oid": "69d4eb12b877594bc57188f4"}, "test_id": "T0039", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4o", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-4o", "duration": 12.178542613983154, "timestamp": "2025-09-30T15:08:41.644596", "parsed": {"metadata": {"send_date": ["1932-09-07"], "letter_title": ["Personenschifffahrt"], "sender_persons": ["Basler Rheinschiffahrt Aktiengesellschaft"], "receiver_persons": ["Dr. M. Vischer-von Planta"]}}, "text": "", "raw_response": {"id": "chatcmpl-CLUNcFGCP3BIBzuaHFgMBohrmOo6X", "model": "gpt-4o-2024-08-06", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\"metadata\":{\"send_date\":[\"1932-09-07\"],\"letter_title\":[\"Personenschifffahrt\"],\"sender_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft\"],\"receiver_persons\":[\"Dr. M. Vischer-von Planta\"]}}", "role": "assistant"}}], "usage": {"prompt_tokens": 2787, "completion_tokens": 54, "total_tokens": 2841}}, "usage": {"input_tokens": 2787, "output_tokens": 54, "total_tokens": 2841}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.56, "f1_micro": 0.52, "cost_summary": {"total_input_tokens": 63939, "total_output_tokens": 1572, "total_tokens": 65511, "input_cost_usd": 0.159847, "output_cost_usd": 0.01572, "total_cost_usd": 0.175567, "pricing_date": "2025-09-30", "input_price_per_million": 2.5, "output_price_per_million": 10.0}}, "normalized_score": 56.00000000000001}, {"_id": {"$oid": "69d4eb12b877594bc57188f8"}, "test_id": "T0038", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4o", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-4o", "duration": 4.672186374664307, "timestamp": "2025-09-30T15:04:57.597505", "parsed": {"metadata": {"send_date": ["1933-08-15"], "letter_title": null, "sender_persons": ["Basler Personenschifffahrtsgesellschaft"], "receiver_persons": ["Basler Rheinschiffahrt A.-G."]}}, "text": "", "raw_response": {"id": "chatcmpl-CLUK7ryRH1vMMjHqPgTZCMyXBBzBa", "model": "gpt-4o-2024-08-06", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\"metadata\":{\"send_date\":[\"1933-08-15\"],\"letter_title\":null,\"sender_persons\":[\"Basler Personenschifffahrtsgesellschaft\"],\"receiver_persons\":[\"Basler Rheinschiffahrt A.-G.\"]}}", "role": "assistant"}}], "usage": {"prompt_tokens": 1257, "completion_tokens": 51, "total_tokens": 1308}}, "usage": {"input_tokens": 1257, "output_tokens": 51, "total_tokens": 1308}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.4, "f1_micro": 0.5, "cost_summary": {"total_input_tokens": 39075, "total_output_tokens": 1169, "total_tokens": 40244, "input_cost_usd": 0.097687, "output_cost_usd": 0.01169, "total_cost_usd": 0.109377, "pricing_date": "2025-09-30", "input_price_per_million": 2.5, "output_price_per_million": 10.0}}, "normalized_score": 40.0}, {"_id": {"$oid": "69d4eb12b877594bc57188fa"}, "test_id": "T0103", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-sonnet-4-20250514", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "anthropic", "model": "claude-sonnet-4-20250514", "duration": 2.48960280418396, "timestamp": "2025-09-30T19:25:09.107886", "parsed": {"metadata": {"send_date": ["1928-02-27"], "letter_title": null, "sender_persons": null, "receiver_persons": ["Basler Rheinschifffahrt A.-G."]}}, "text": "", "raw_response": {"id": "msg_012r3kaiAApS1VpM8F1T45tF", "model": "claude-sonnet-4-20250514", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01Cmp9tc2Yo4QPU6aZCdkL7n", "name": "extract_structured_data", "input": {"metadata": {"letter_title": null, "send_date": ["1928-02-27"], "sender_persons": null, "receiver_persons": ["Basler Rheinschifffahrt A.-G."]}}}], "stop_reason": "tool_use", "usage": {"input_tokens": 1904, "output_tokens": 90}}, "usage": {"input_tokens": 1904, "output_tokens": 90, "total_tokens": 1994}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.31, "f1_micro": 0.31, "cost_summary": {"total_input_tokens": 148093, "total_output_tokens": 5863, "total_tokens": 153956, "input_cost_usd": 0.444279, "output_cost_usd": 0.087945, "total_cost_usd": 0.532224, "pricing_date": "2025-09-30", "input_price_per_million": 3.0, "output_price_per_million": 15.0}}, "normalized_score": 31.0}, {"_id": {"$oid": "69d4eb12b877594bc57188fe"}, "test_id": "T0010", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4o", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-4o", "duration": 3.374835729598999, "timestamp": "2025-09-30T14:22:15.007277", "parsed": {"metadata": {"send_date": ["1935-08-17"], "letter_title": null, "sender_persons": null, "receiver_persons": ["Fritz Ritter"]}}, "text": "", "raw_response": {"id": "chatcmpl-CLTeo1nlZX3ffCmNpjwyCmC2j5Hu0", "model": "gpt-4o-2024-08-06", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\"metadata\":{\"send_date\":[\"1935-08-17\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":[\"Fritz Ritter\"]}}", "role": "assistant"}}], "usage": {"prompt_tokens": 1257, "completion_tokens": 34, "total_tokens": 1291}}, "usage": {"input_tokens": 1257, "output_tokens": 34, "total_tokens": 1291}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.52, "f1_micro": 0.53, "cost_summary": {"total_input_tokens": 103014, "total_output_tokens": 2689, "total_tokens": 105703, "input_cost_usd": 0.257535, "output_cost_usd": 0.02689, "total_cost_usd": 0.284425, "pricing_date": "2025-09-30", "input_price_per_million": 2.5, "output_price_per_million": 10.0}}, "normalized_score": 52.0}, {"_id": {"$oid": "69d4eb12b877594bc5718900"}, "test_id": "T0044", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.0-flash", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "genai", "model": "gemini-2.0-flash", "duration": 1.9633047580718994, "timestamp": "2025-09-30T15:15:04.191606", "parsed": {"metadata": {"send_date": ["1928-03-24"], "letter_title": ["null"], "sender_persons": ["b.w.", "Basler Personenschifffahrtsgesellschaft"], "receiver_persons": ["Basler Rheinschiffahrt A.-G."]}}, "text": "{\n \"metadata\": {\n \"send_date\": [\n \"1928-03-24\"\n ],\n \"letter_title\": [\n \"null\"\n ],\n \"sender_persons\": [\n \"b.w.\",\n \"Basler Personenschifffahrtsgesellschaft\"\n ],\n \"receiver_persons\": [\n \"Basler Rheinschiffahrt A.-G.\"\n ]\n }\n}", "raw_response": {"text": "{\n \"metadata\": {\n \"send_date\": [\n \"1928-03-24\"\n ],\n \"letter_title\": [\n \"null\"\n ],\n \"sender_persons\": [\n \"b.w.\",\n \"Basler Personenschifffahrtsgesellschaft\"\n ],\n \"receiver_persons\": [\n \"Basler Rheinschiffahrt A.-G.\"\n ]\n }\n}", "usage_metadata": {"prompt_token_count": 878, "candidates_token_count": 108, "total_token_count": 986}}, "usage": {"input_tokens": 878, "output_tokens": 108, "total_tokens": 986}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.51, "f1_micro": 0.61, "cost_summary": {"total_input_tokens": 45944, "total_output_tokens": 2264, "total_tokens": 48208, "input_cost_usd": 0.004594, "output_cost_usd": 0.000906, "total_cost_usd": 0.0055, "pricing_date": "2025-09-30", "input_price_per_million": 0.1, "output_price_per_million": 0.4}}, "normalized_score": 51.0}, {"_id": {"$oid": "69d4eb12b877594bc5718905"}, "test_id": "T0126", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-pro", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "genai", "model": "gemini-2.5-pro", "duration": 7.527446269989014, "timestamp": "2025-09-30T23:22:09.738143", "parsed": {"metadata": {"send_date": ["1935-08-16"], "letter_title": null, "sender_persons": ["Basler Rheinschifffahrt Aktiengesellschaft"], "receiver_persons": ["Basler Personenschifffahrts-Gesellschaft"]}}, "text": "{\n\"metadata\": {\n\"send_date\": [\n\"1935-08-16\"\n],\n\"letter_title\": null,\n\"sender_persons\": [\n\"Basler Rheinschifffahrt Aktiengesellschaft\"\n],\n\"receiver_persons\": [\n\"Basler Personenschifffahrts-Gesellschaft\"\n]\n}\n}", "raw_response": {"text": "{\n\"metadata\": {\n\"send_date\": [\n\"1935-08-16\"\n],\n\"letter_title\": null,\n\"sender_persons\": [\n\"Basler Rheinschifffahrt Aktiengesellschaft\"\n],\n\"receiver_persons\": [\n\"Basler Personenschifffahrts-Gesellschaft\"\n]\n}\n}", "usage_metadata": {"prompt_token_count": 573, "candidates_token_count": 84, "total_token_count": 1398}}, "usage": {"input_tokens": 573, "output_tokens": 84, "total_tokens": 1398}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.58, "f1_micro": 0.53, "cost_summary": {"total_input_tokens": 26365, "total_output_tokens": 2876, "total_tokens": 29241, "input_cost_usd": 0.032956, "output_cost_usd": 0.02876, "total_cost_usd": 0.061716, "pricing_date": "2025-09-30", "input_price_per_million": 1.25, "output_price_per_million": 10.0}}, "normalized_score": 57.99999999999999}, {"_id": {"$oid": "69d4eb12b877594bc5718906"}, "test_id": "T0197", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-flash", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "genai", "model": "gemini-2.5-flash", "duration": 17.17101740837097, "timestamp": "2025-09-30T23:20:23.484609", "parsed": {"metadata": {"send_date": ["1928-04-04"], "letter_title": ["EINSCHREIBEN"], "sender_persons": ["Basler Personenschifffahrtgesellschaft"], "receiver_persons": ["Basler Rheinschifffahrt-Aktiengesellschaft"]}}, "text": "{\"metadata\": {\"send_date\": [\"1928-04-04\"], \"letter_title\": [\"EINSCHREIBEN\"], \"sender_persons\": [\"Basler Personenschifffahrtgesellschaft\"], \"receiver_persons\": [\"Basler Rheinschifffahrt-Aktiengesellschaft\"]}}", "raw_response": {"text": "{\"metadata\": {\"send_date\": [\"1928-04-04\"], \"letter_title\": [\"EINSCHREIBEN\"], \"sender_persons\": [\"Basler Personenschifffahrtgesellschaft\"], \"receiver_persons\": [\"Basler Rheinschifffahrt-Aktiengesellschaft\"]}}", "usage_metadata": {"prompt_token_count": 832, "candidates_token_count": 65, "total_token_count": 2945}}, "usage": {"input_tokens": 832, "output_tokens": 65, "total_tokens": 2945}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.53, "f1_micro": 0.63, "cost_summary": {"total_input_tokens": 16915, "total_output_tokens": 1469, "total_tokens": 18384, "input_cost_usd": 0.005075, "output_cost_usd": 0.003672, "total_cost_usd": 0.008747, "pricing_date": "2025-09-30", "input_price_per_million": 0.3, "output_price_per_million": 2.5}}, "normalized_score": 53.0}, {"_id": {"$oid": "69d4eb12b877594bc5718907"}, "test_id": "T0061", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "pixtral-large-2411", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "mistral", "model": "pixtral-large-latest", "duration": 1.8600232601165771, "timestamp": "2025-09-30T15:24:32.903523", "text": "{\n \"metadata\": {\n \"letter_title\": [null],\n \"send_date\": [\"1928-05-31\"],\n \"sender_persons\": [\"Herr Professor\"],\n \"receiver_persons\": [\"Herrn Dr. Max Vischer\"]\n }\n}", "raw_response": {"id": "141d6a38ebfe4c5797475b841b085ef3", "model": "pixtral-large-latest", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"letter_title\": [null],\n \"send_date\": [\"1928-05-31\"],\n \"sender_persons\": [\"Herr Professor\"],\n \"receiver_persons\": [\"Herrn Dr. Max Vischer\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 3614, "completion_tokens": 74, "total_tokens": 3688}}, "usage": {"input_tokens": 3614, "output_tokens": 74, "total_tokens": 3688}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.38, "f1_micro": 0.34, "cost_summary": {"total_input_tokens": 208842, "total_output_tokens": 2859, "total_tokens": 211701, "input_cost_usd": 0.417684, "output_cost_usd": 0.017154, "total_cost_usd": 0.434838, "pricing_date": "2025-09-30", "input_price_per_million": 2.0, "output_price_per_million": 6.0}}, "normalized_score": 38.0}, {"_id": {"$oid": "69d4eb12b877594bc5718908"}, "test_id": "T0068", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4.1", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-4.1", "duration": 2.8923115730285645, "timestamp": "2025-09-30T17:55:43.479647", "parsed": {"metadata": {"send_date": ["1923-08-15"], "letter_title": ["null"], "sender_persons": ["Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["Basler Rheinschiffahrts A.-G."]}}, "text": "", "raw_response": {"id": "chatcmpl-CLWzO31Z2Vr5lOg2ojpT6IbXloqlq", "model": "gpt-4.1-2025-04-14", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1923-08-15\"],\n \"letter_title\": [ \"null\" ],\n \"sender_persons\": [\"Basler Personenschiffahrtsgesellschaft\"],\n \"receiver_persons\": [\"Basler Rheinschiffahrts A.-G.\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 1257, "completion_tokens": 67, "total_tokens": 1324}}, "usage": {"input_tokens": 1257, "output_tokens": 67, "total_tokens": 1324}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.41, "f1_micro": 0.5, "cost_summary": {"total_input_tokens": 39075, "total_output_tokens": 1548, "total_tokens": 40623, "input_cost_usd": 0.07815, "output_cost_usd": 0.012384, "total_cost_usd": 0.090534, "pricing_date": "2025-09-30", "input_price_per_million": 2.0, "output_price_per_million": 8.0}}, "normalized_score": 41.0}, {"_id": {"$oid": "69d4eb12b877594bc5718909"}, "test_id": "T0109", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-5", "duration": 40.55900049209595, "timestamp": "2025-09-30T20:48:30.816790", "parsed": {"metadata": {"send_date": ["1928-07-14"], "letter_title": null, "sender_persons": null, "receiver_persons": null}}, "text": "", "raw_response": {"id": "chatcmpl-CLZg73SIYRBQtN1Y8iu4CX0yRQqyJ", "model": "gpt-5-2025-08-07", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\"metadata\":{\"send_date\":[\"1928-07-14\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":null}}", "role": "assistant"}}], "usage": {"prompt_tokens": 1118, "completion_tokens": 1643, "total_tokens": 2761}}, "usage": {"input_tokens": 1118, "output_tokens": 1643, "total_tokens": 2761}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.62, "f1_micro": 0.78, "cost_summary": {"total_input_tokens": 34250, "total_output_tokens": 43948, "total_tokens": 78198, "input_cost_usd": 0.042813, "output_cost_usd": 0.43948, "total_cost_usd": 0.482293, "pricing_date": "2025-09-30", "input_price_per_million": 1.25, "output_price_per_million": 10.0}}, "normalized_score": 62.0}, {"_id": {"$oid": "69d4eb12b877594bc571890d"}, "test_id": "T0105", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-sonnet-4-20250514", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "anthropic", "model": "claude-sonnet-4-20250514", "duration": 3.1751368045806885, "timestamp": "2025-09-30T19:30:05.593616", "parsed": {"metadata": {"send_date": ["1928-04-04"], "letter_title": ["Betrifft Kauf \"Rheinfelden\""], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Basler Personenschiffahrtsgesellschaft"]}}, "text": "", "raw_response": {"id": "msg_01T7vJBFSRSTYUSkMuZUUobg", "model": "claude-sonnet-4-20250514", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_0181xngBSWmH98UkaKrRv3y4", "name": "extract_structured_data", "input": {"metadata": {"letter_title": ["Betrifft Kauf \"Rheinfelden\""], "send_date": ["1928-04-04"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Basler Personenschiffahrtsgesellschaft"]}}}], "stop_reason": "tool_use", "usage": {"input_tokens": 2869, "output_tokens": 119}}, "usage": {"input_tokens": 2869, "output_tokens": 119, "total_tokens": 2988}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.36, "f1_micro": 0.34, "cost_summary": {"total_input_tokens": 90843, "total_output_tokens": 3336, "total_tokens": 94179, "input_cost_usd": 0.272529, "output_cost_usd": 0.05004, "total_cost_usd": 0.322569, "pricing_date": "2025-09-30", "input_price_per_million": 3.0, "output_price_per_million": 15.0}}, "normalized_score": 36.0}, {"_id": {"$oid": "69d4eb12b877594bc571890f"}, "test_id": "T0075", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4.1-nano", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-4.1-nano", "duration": 2.329655885696411, "timestamp": "2025-09-30T18:07:22.541124", "parsed": {"metadata": {"send_date": ["1926-02-16"], "letter_title": ["Letter to Herr Christ"], "sender_persons": ["Basler Rhein Schiffahrt-Aktiengesellschaft"], "receiver_persons": ["Herr Christ"]}}, "text": "", "raw_response": {"id": "chatcmpl-CLXAhrUDVtLSuGLycz6YdoWIwsV1T", "model": "gpt-4.1-nano-2025-04-14", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\"metadata\":{\"send_date\":[\"1926-02-16\"],\"letter_title\":[\"Letter to Herr Christ\"],\"sender_persons\":[\"Basler Rhein Schiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Herr Christ\"]}}", "role": "assistant"}}], "usage": {"prompt_tokens": 5928, "completion_tokens": 46, "total_tokens": 5974}}, "usage": {"input_tokens": 5928, "output_tokens": 46, "total_tokens": 5974}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.53, "f1_micro": 0.47, "cost_summary": {"total_input_tokens": 129900, "total_output_tokens": 1667, "total_tokens": 131567, "input_cost_usd": 0.01299, "output_cost_usd": 0.000667, "total_cost_usd": 0.013657, "pricing_date": "2025-09-30", "input_price_per_million": 0.1, "output_price_per_million": 0.4}}, "normalized_score": 53.0}, {"_id": {"$oid": "69d4eb12b877594bc5718912"}, "test_id": "T0115", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5-nano", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-5-nano", "duration": 22.297992944717407, "timestamp": "2025-09-30T22:27:37.679576", "parsed": {"metadata": {"send_date": ["1928-04-04"], "letter_title": ["null"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["null"]}}, "text": "", "raw_response": {"id": "chatcmpl-CLbEKcRhuSuuqbesKk3UUOJpnGbtI", "model": "gpt-5-nano-2025-08-07", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1928-04-04\"],\n \"letter_title\": [\"null\"],\n \"sender_persons\": [\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\n \"receiver_persons\": [\"null\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 2698, "completion_tokens": 3974, "total_tokens": 6672}}, "usage": {"input_tokens": 2698, "output_tokens": 3974, "total_tokens": 6672}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.47, "f1_micro": 0.57, "cost_summary": {"total_input_tokens": 50875, "total_output_tokens": 68357, "total_tokens": 119232, "input_cost_usd": 0.002544, "output_cost_usd": 0.027343, "total_cost_usd": 0.029887, "pricing_date": "2025-09-30", "input_price_per_million": 0.05, "output_price_per_million": 0.4}}, "normalized_score": 47.0}, {"_id": {"$oid": "69d4eb12b877594bc5718913"}, "test_id": "T0020", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.0-flash-lite", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "genai", "model": "gemini-2.0-flash-lite", "duration": 1.779918909072876, "timestamp": "2025-09-30T14:39:07.662498", "parsed": {"metadata": {"send_date": ["1933-07-04"], "letter_title": ["null"], "sender_persons": ["J. B. Fischer", "Arthur Cellinger"], "receiver_persons": ["null"]}}, "text": "{\n \"metadata\": {\n \"send_date\": [\n \"1933-07-04\"\n ],\n \"letter_title\": [\n \"null\"\n ],\n \"sender_persons\": [\n \"J. B. Fischer\",\n \"Arthur Cellinger\"\n ],\n \"receiver_persons\": [\n \"null\"\n ]\n }\n}", "raw_response": {"text": "{\n \"metadata\": {\n \"send_date\": [\n \"1933-07-04\"\n ],\n \"letter_title\": [\n \"null\"\n ],\n \"sender_persons\": [\n \"J. B. Fischer\",\n \"Arthur Cellinger\"\n ],\n \"receiver_persons\": [\n \"null\"\n ]\n }\n}", "usage_metadata": {"prompt_token_count": 878, "candidates_token_count": 96, "total_token_count": 974}}, "usage": {"input_tokens": 878, "output_tokens": 96, "total_tokens": 974}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.52, "f1_micro": 0.54, "cost_summary": {"total_input_tokens": 97002, "total_output_tokens": 5427, "total_tokens": 102429, "input_cost_usd": 0.007275, "output_cost_usd": 0.001628, "total_cost_usd": 0.008903, "pricing_date": "2025-09-30", "input_price_per_million": 0.075, "output_price_per_million": 0.3}}, "normalized_score": 52.0}, {"_id": {"$oid": "69d4eb12b877594bc5718916"}, "test_id": "T0078", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4o-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-4o-mini", "duration": 2.9531123638153076, "timestamp": "2025-09-30T18:16:14.159129", "parsed": {"metadata": {"send_date": ["1932-12-19"], "letter_title": ["Betr. Personenschifffahrt"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Dr. M. Vischer - von Planta"]}}, "text": "", "raw_response": {"id": "chatcmpl-CLXJFCfVkBs7juIlXPw4EFUoOqUe0", "model": "gpt-4o-mini-2024-07-18", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1932-12-19\"],\n \"letter_title\": [\"Betr. Personenschifffahrt\"],\n \"sender_persons\": [\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\n \"receiver_persons\": [\"Dr. M. Vischer - von Planta\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 25993, "completion_tokens": 73, "total_tokens": 26066}}, "usage": {"input_tokens": 25993, "output_tokens": 73, "total_tokens": 26066}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.57, "f1_micro": 0.51, "cost_summary": {"total_input_tokens": 1622307, "total_output_tokens": 2243, "total_tokens": 1624550, "input_cost_usd": 0.243346, "output_cost_usd": 0.001346, "total_cost_usd": 0.244692, "pricing_date": "2025-09-30", "input_price_per_million": 0.15, "output_price_per_million": 0.6}}, "normalized_score": 56.99999999999999}, {"_id": {"$oid": "69d4eb12b877594bc5718919"}, "test_id": "T0118", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-opus-4-1-20250805", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "anthropic", "model": "claude-opus-4-1-20250805", "duration": 3.7988643646240234, "timestamp": "2025-09-30T22:43:37.697681", "parsed": {"metadata": {"send_date": ["1988-07-14"], "letter_title": null, "sender_persons": ["Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["Basler Nachrichten"]}}, "text": "", "raw_response": {"id": "msg_01Me9R9mdXUauRVxgKLGP4JZ", "model": "claude-opus-4-1-20250805", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_014k1vQuZLyZpLcfQjwjdjm6", "name": "extract_structured_data", "input": {"metadata": {"letter_title": null, "send_date": ["1988-07-14"], "sender_persons": ["Basler Personenschiffahrtsgesellschaft"], "receiver_persons": ["Basler Nachrichten"]}}}], "stop_reason": "tool_use", "usage": {"input_tokens": 1904, "output_tokens": 96}}, "usage": {"input_tokens": 1904, "output_tokens": 96, "total_tokens": 2000}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.39, "f1_micro": 0.44, "cost_summary": {"total_input_tokens": 57250, "total_output_tokens": 2523, "total_tokens": 59773, "input_cost_usd": 0.85875, "output_cost_usd": 0.189225, "total_cost_usd": 1.047975, "pricing_date": "2025-09-30", "input_price_per_million": 15.0, "output_price_per_million": 75.0}}, "normalized_score": 39.0}, {"_id": {"$oid": "69d4eb12b877594bc571891a"}, "test_id": "T0074", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4.1-nano", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-4.1-nano", "duration": 4.0607335567474365, "timestamp": "2025-09-30T18:06:24.550873", "parsed": {"metadata": {"send_date": ["1926-08-13"], "letter_title": ["Best\u00e4tigung der Nutzung der Landungsstege"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Herrn Dr. Max Vischer"]}}, "text": "", "raw_response": {"id": "chatcmpl-CLX9jgWgylq2PAhkSb4yzhQxYZi5p", "model": "gpt-4.1-nano-2025-04-14", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\"metadata\":{\"send_date\":[\"1926-08-13\"],\"letter_title\":[\"Best\u00e4tigung der Nutzung der Landungsstege\"],\"sender_persons\":[\"Basler Rheinschiffahrt-Aktiengesellschaft\"],\"receiver_persons\":[\"Herrn Dr. Max Vischer\"]}}", "role": "assistant"}}], "usage": {"prompt_tokens": 5928, "completion_tokens": 58, "total_tokens": 5986}}, "usage": {"input_tokens": 5928, "output_tokens": 58, "total_tokens": 5986}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.37, "f1_micro": 0.5, "cost_summary": {"total_input_tokens": 75720, "total_output_tokens": 1240, "total_tokens": 76960, "input_cost_usd": 0.007572, "output_cost_usd": 0.000496, "total_cost_usd": 0.008068, "pricing_date": "2025-09-30", "input_price_per_million": 0.1, "output_price_per_million": 0.4}}, "normalized_score": 37.0}, {"_id": {"$oid": "69d4eb12b877594bc571891c"}, "test_id": "T0076", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4o-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-4o-mini", "duration": 2.450058937072754, "timestamp": "2025-09-30T18:10:31.311173", "parsed": {"metadata": {"send_date": ["1928-03-26"], "letter_title": ["An die Basler Rheinschifffahrt A.-G."], "sender_persons": ["Basler Personenschifffahrt"], "receiver_persons": ["Basler Rheinschifffahrt A.-G."]}}, "text": "", "raw_response": {"id": "chatcmpl-CLXDjhcQDnuoVKaOT90um2JFPtFrh", "model": "gpt-4o-mini-2024-07-18", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1928-03-26\"],\n \"letter_title\": [\"An die Basler Rheinschifffahrt A.-G.\"],\n \"sender_persons\": [\"Basler Personenschifffahrt\"],\n \"receiver_persons\": [\"Basler Rheinschifffahrt A.-G.\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 25993, "completion_tokens": 77, "total_tokens": 26070}}, "usage": {"input_tokens": 25993, "output_tokens": 77, "total_tokens": 26070}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.55, "f1_micro": 0.54, "cost_summary": {"total_input_tokens": 2527142, "total_output_tokens": 3970, "total_tokens": 2531112, "input_cost_usd": 0.379071, "output_cost_usd": 0.002382, "total_cost_usd": 0.381453, "pricing_date": "2025-09-30", "input_price_per_million": 0.15, "output_price_per_million": 0.6}}, "normalized_score": 55.00000000000001}, {"_id": {"$oid": "69d4eb12b877594bc571891d"}, "test_id": "T0113", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-5-mini", "duration": 19.441518545150757, "timestamp": "2025-09-30T22:06:25.078996", "parsed": {"metadata": {"send_date": ["1932-11-24"], "letter_title": ["null"], "sender_persons": ["Dr. Max Vischer"], "receiver_persons": ["A. Oettinger"]}}, "text": "", "raw_response": {"id": "chatcmpl-CLatqVVEh9SlHmq9iuN5lHnAcEMHj", "model": "gpt-5-mini-2025-08-07", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\"metadata\":{\"send_date\":[\"1932-11-24\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"Dr. Max Vischer\"],\"receiver_persons\":[\"A. Oettinger\"]}}", "role": "assistant"}}], "usage": {"prompt_tokens": 1373, "completion_tokens": 1078, "total_tokens": 2451}}, "usage": {"input_tokens": 1373, "output_tokens": 1078, "total_tokens": 2451}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.55, "f1_micro": 0.51, "cost_summary": {"total_input_tokens": 71371, "total_output_tokens": 34477, "total_tokens": 105848, "input_cost_usd": 0.017843, "output_cost_usd": 0.068954, "total_cost_usd": 0.086797, "pricing_date": "2025-09-30", "input_price_per_million": 0.25, "output_price_per_million": 2.0}}, "normalized_score": 55.00000000000001}, {"_id": {"$oid": "69d4eb12b877594bc571891e"}, "test_id": "T0023", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "mistral", "model": "pixtral-large-2411", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history. You only return valid JSON an no other text.", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "mistral", "model": "pixtral-large-latest", "duration": 2.7848877906799316, "timestamp": "2025-09-30T14:39:52.605389", "parsed": {"metadata": {"send_date": ["1988-07-14"], "letter_title": ["Redaktion der 'Basler Nachrichten'"], "sender_persons": ["Basler Personenschiffsgesellschaft"], "receiver_persons": ["null"]}}, "text": "", "raw_response": {"id": "41aca878d7714462be1888f3d90ea542", "model": "pixtral-large-latest", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1988-07-14\"],\n \"letter_title\": [\"Redaktion der 'Basler Nachrichten'\"],\n \"sender_persons\": [\"Basler Personenschiffsgesellschaft\"],\n \"receiver_persons\": [\"null\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 3614, "completion_tokens": 81, "total_tokens": 3695}}, "usage": {"input_tokens": 3614, "output_tokens": 81, "total_tokens": 3695}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.36, "f1_micro": 0.36, "cost_summary": {"total_input_tokens": 329272, "total_output_tokens": 4967, "total_tokens": 334239, "input_cost_usd": 0.658544, "output_cost_usd": 0.029802, "total_cost_usd": 0.688346, "pricing_date": "2025-09-30", "input_price_per_million": 2.0, "output_price_per_million": 6.0}}, "normalized_score": 36.0}, {"_id": {"$oid": "69d4eb12b877594bc5718920"}, "test_id": "T0100", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-opus-4-20250514", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "anthropic", "model": "claude-opus-4-20250514", "duration": 5.547164440155029, "timestamp": "2025-09-30T19:14:40.306848", "parsed": {"metadata": {"send_date": ["1926-03-24"], "letter_title": null, "sender_persons": ["BASLER RHEINSCHIFFAHRT-AKTIENGESELLSCHAFT"], "receiver_persons": ["Herrn B. Christ - Wackernagel", "Fa. Paravicini,Christ & Co."]}}, "text": "", "raw_response": {"id": "msg_01U3MCx1eng3vGtZZky3MtnS", "model": "claude-opus-4-20250514", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01SXF4H9ZE2LimUPS7agPPDL", "name": "extract_structured_data", "input": {"metadata": {"letter_title": null, "sender_persons": ["BASLER RHEINSCHIFFAHRT-AKTIENGESELLSCHAFT"], "send_date": ["1926-03-24"], "receiver_persons": ["Herrn B. Christ - Wackernagel", "Fa. Paravicini,Christ & Co."]}}}], "stop_reason": "tool_use", "usage": {"input_tokens": 1904, "output_tokens": 121}}, "usage": {"input_tokens": 1904, "output_tokens": 121, "total_tokens": 2025}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.36, "f1_micro": 0.37, "cost_summary": {"total_input_tokens": 148093, "total_output_tokens": 6063, "total_tokens": 154156, "input_cost_usd": 2.221395, "output_cost_usd": 0.454725, "total_cost_usd": 2.67612, "pricing_date": "2025-09-30", "input_price_per_million": 15.0, "output_price_per_million": 75.0}}, "normalized_score": 36.0}, {"_id": {"$oid": "69d4eb12b877594bc5718922"}, "test_id": "T0108", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-5", "duration": 41.835389614105225, "timestamp": "2025-09-30T19:58:56.108543", "parsed": {"metadata": {"send_date": ["1928-05-03"], "letter_title": null, "sender_persons": null, "receiver_persons": ["Dr. Max Vischer"]}}, "text": "", "raw_response": {"id": "chatcmpl-CLYu7fVn37naFMfQ10nnztiIwp3vB", "model": "gpt-5-2025-08-07", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\"metadata\":{\"send_date\":[\"1928-05-03\"],\"letter_title\":null,\"sender_persons\":null,\"receiver_persons\":[\"Dr. Max Vischer\"]}}", "role": "assistant"}}], "usage": {"prompt_tokens": 1118, "completion_tokens": 1777, "total_tokens": 2895}}, "usage": {"input_tokens": 1118, "output_tokens": 1777, "total_tokens": 2895}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.67, "f1_micro": 0.71, "cost_summary": {"total_input_tokens": 89556, "total_output_tokens": 118630, "total_tokens": 208186, "input_cost_usd": 0.111945, "output_cost_usd": 1.1863, "total_cost_usd": 1.298245, "pricing_date": "2025-09-30", "input_price_per_million": 1.25, "output_price_per_million": 10.0}}, "normalized_score": 67.0}, {"_id": {"$oid": "69d4eb12b877594bc5718923"}, "test_id": "T0077", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4o-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-4o-mini", "duration": 3.5150227546691895, "timestamp": "2025-09-30T18:13:15.696653", "parsed": {"metadata": {"send_date": ["1928-03-24"], "letter_title": ["Verkauf"], "sender_persons": ["Basler Rheinschiffahrt A.-G."], "receiver_persons": ["Basler Rheinschiffahrt A.-G."]}}, "text": "", "raw_response": {"id": "chatcmpl-CLXGM6XBeeFftoQf2orb6R3T3q7uM", "model": "gpt-4o-mini-2024-07-18", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1928-03-24\"],\n \"letter_title\": [\"Verkauf\"],\n \"sender_persons\": [\"Basler Rheinschiffahrt A.-G.\"],\n \"receiver_persons\": [\"Basler Rheinschiffahrt A.-G.\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 51494, "completion_tokens": 69, "total_tokens": 51563}}, "usage": {"input_tokens": 51494, "output_tokens": 69, "total_tokens": 51563}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.44, "f1_micro": 0.53, "cost_summary": {"total_input_tokens": 904835, "total_output_tokens": 1729, "total_tokens": 906564, "input_cost_usd": 0.135725, "output_cost_usd": 0.001037, "total_cost_usd": 0.136763, "pricing_date": "2025-09-30", "input_price_per_million": 0.15, "output_price_per_million": 0.6}}, "normalized_score": 44.0}, {"_id": {"$oid": "69d4eb12b877594bc5718925"}, "test_id": "T0125", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.5-pro", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "genai", "model": "gemini-2.5-pro", "duration": 5.176327705383301, "timestamp": "2025-09-30T23:15:20.681914", "parsed": {"metadata": {"send_date": ["1928-03-24"], "letter_title": ["Verkauf des Schiffes Rheinfelden"], "sender_persons": ["Basler Personenschiffahrtgesellschaft"], "receiver_persons": ["Basler Rheinschiffahrt A.-G."]}}, "text": "{\n\"metadata\": {\n\"send_date\": [\n\"1928-03-24\"\n],\n\"letter_title\": [\n\"Verkauf des Schiffes Rheinfelden\"\n],\n\"sender_persons\": [\n\"Basler Personenschiffahrtgesellschaft\"\n],\n\"receiver_persons\": [\n\"Basler Rheinschiffahrt A.-G.\"\n]\n}\n}", "raw_response": {"text": "{\n\"metadata\": {\n\"send_date\": [\n\"1928-03-24\"\n],\n\"letter_title\": [\n\"Verkauf des Schiffes Rheinfelden\"\n],\n\"sender_persons\": [\n\"Basler Personenschiffahrtgesellschaft\"\n],\n\"receiver_persons\": [\n\"Basler Rheinschiffahrt A.-G.\"\n]\n}\n}", "usage_metadata": {"prompt_token_count": 832, "candidates_token_count": 93, "total_token_count": 1326}}, "usage": {"input_tokens": 832, "output_tokens": 93, "total_tokens": 1326}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.52, "f1_micro": 0.62, "cost_summary": {"total_input_tokens": 16915, "total_output_tokens": 2147, "total_tokens": 19062, "input_cost_usd": 0.021144, "output_cost_usd": 0.02147, "total_cost_usd": 0.042614, "pricing_date": "2025-09-30", "input_price_per_million": 1.25, "output_price_per_million": 10.0}}, "normalized_score": 52.0}, {"_id": {"$oid": "69d4eb12b877594bc5718928"}, "test_id": "T0102", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-opus-4-20250514", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "anthropic", "model": "claude-opus-4-20250514", "duration": 5.645486116409302, "timestamp": "2025-09-30T19:22:03.030090", "parsed": {"metadata": {"send_date": ["1928-02-18"], "letter_title": null, "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Vorstand der Basler Personenschiffahrts-Gesellschaft"]}}, "text": "", "raw_response": {"id": "msg_01T7meAfFooTdUGBDzFfmhD9", "model": "claude-opus-4-20250514", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01YQuvriDBv5hu6R9y43HspJ", "name": "extract_structured_data", "input": {"metadata": {"letter_title": null, "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "send_date": ["1928-02-18"], "receiver_persons": ["Vorstand der Basler Personenschiffahrts-Gesellschaft"]}}}], "stop_reason": "tool_use", "usage": {"input_tokens": 6729, "output_tokens": 114}}, "usage": {"input_tokens": 6729, "output_tokens": 114, "total_tokens": 6843}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.32, "f1_micro": 0.3, "cost_summary": {"total_input_tokens": 90843, "total_output_tokens": 3500, "total_tokens": 94343, "input_cost_usd": 1.362645, "output_cost_usd": 0.2625, "total_cost_usd": 1.625145, "pricing_date": "2025-09-30", "input_price_per_million": 15.0, "output_price_per_million": 75.0}}, "normalized_score": 32.0}, {"_id": {"$oid": "69d4eb12b877594bc571892b"}, "test_id": "T0012", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4o-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-4o-mini", "duration": 4.013835668563843, "timestamp": "2025-09-30T14:25:19.740387", "parsed": {"metadata": {"send_date": ["1932-10-04"], "letter_title": ["Letter to Dr. Max Vischer"], "sender_persons": ["Basler Rheinschiffahrt Aktiengesellschaft"], "receiver_persons": ["Dr. Max Vischer"]}}, "text": "", "raw_response": {"id": "chatcmpl-CLThmEaL1ikfK7QAiT4pZMWgpGU5h", "model": "gpt-4o-mini-2024-07-18", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1932-10-04\"],\n \"letter_title\": [\"Letter to Dr. Max Vischer\"],\n \"sender_persons\": [\"Basler Rheinschiffahrt Aktiengesellschaft\"],\n \"receiver_persons\": [\"Dr. Max Vischer\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 76995, "completion_tokens": 66, "total_tokens": 77061}}, "usage": {"input_tokens": 76995, "output_tokens": 66, "total_tokens": 77061}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.54, "f1_micro": 0.55, "cost_summary": {"total_input_tokens": 2527142, "total_output_tokens": 3935, "total_tokens": 2531077, "input_cost_usd": 0.379071, "output_cost_usd": 0.002361, "total_cost_usd": 0.381432, "pricing_date": "2025-09-30", "input_price_per_million": 0.15, "output_price_per_million": 0.6}}, "normalized_score": 54.0}, {"_id": {"$oid": "69d4eb12b877594bc571892e"}, "test_id": "T0117", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-opus-4-1-20250805", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "anthropic", "model": "claude-opus-4-1-20250805", "duration": 4.361761808395386, "timestamp": "2025-09-30T22:40:01.546125", "parsed": {"metadata": {"send_date": ["1925-08-13"], "letter_title": null, "sender_persons": ["J.A.Ritter"], "receiver_persons": ["Dr. Max Vischer"]}}, "text": "", "raw_response": {"id": "msg_01Lkqud7FAj5mX2jMjhfME2V", "model": "claude-opus-4-1-20250805", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_0165P46cMdD5cTtsnAbvbxtE", "name": "extract_structured_data", "input": {"metadata": {"letter_title": null, "send_date": ["1925-08-13"], "sender_persons": ["J.A.Ritter"], "receiver_persons": ["Dr. Max Vischer"]}}}], "stop_reason": "tool_use", "usage": {"input_tokens": 3834, "output_tokens": 92}}, "usage": {"input_tokens": 3834, "output_tokens": 92, "total_tokens": 3926}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.36, "f1_micro": 0.36, "cost_summary": {"total_input_tokens": 148093, "total_output_tokens": 5876, "total_tokens": 153969, "input_cost_usd": 2.221395, "output_cost_usd": 0.4407, "total_cost_usd": 2.662095, "pricing_date": "2025-09-30", "input_price_per_million": 15.0, "output_price_per_million": 75.0}}, "normalized_score": 36.0}, {"_id": {"$oid": "69d4eb12b877594bc571892f"}, "test_id": "T0070", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4.1-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-4.1-mini", "duration": 1.5398213863372803, "timestamp": "2025-09-30T17:59:45.813827", "parsed": {"metadata": {"send_date": ["1928-05-05"], "letter_title": ["Abschrift"], "sender_persons": ["Herr Direktor W. Stauffacher"], "receiver_persons": ["Basler Rheinschiffahrts-A.G."]}}, "text": "", "raw_response": {"id": "chatcmpl-CLX3KcnlMhBTI9bRlmGeCHSljtYRz", "model": "gpt-4.1-mini-2025-04-14", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\"metadata\":{\"send_date\":[\"1928-05-05\"],\"letter_title\":[ \"Abschrift\"],\"sender_persons\":[\"Herr Direktor W. Stauffacher\"],\"receiver_persons\":[\"Basler Rheinschiffahrts-A.G.\"]}}", "role": "assistant"}}], "usage": {"prompt_tokens": 1686, "completion_tokens": 53, "total_tokens": 1739}}, "usage": {"input_tokens": 1686, "output_tokens": 53, "total_tokens": 1739}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.55, "f1_micro": 0.56, "cost_summary": {"total_input_tokens": 145056, "total_output_tokens": 3089, "total_tokens": 148145, "input_cost_usd": 0.058022, "output_cost_usd": 0.004942, "total_cost_usd": 0.062965, "pricing_date": "2025-09-30", "input_price_per_million": 0.4, "output_price_per_million": 1.6}}, "normalized_score": 55.00000000000001}, {"_id": {"$oid": "69d4eb12b877594bc5718935"}, "test_id": "T0104", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "anthropic", "model": "claude-sonnet-4-20250514", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "anthropic", "model": "claude-sonnet-4-20250514", "duration": 3.3676834106445312, "timestamp": "2025-09-30T19:28:15.968379", "parsed": {"metadata": {"send_date": ["1926-08-12"], "letter_title": null, "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Dr. Max Vischer"]}}, "text": "", "raw_response": {"id": "msg_01AjikEe1DoYJpeJKRchGhXd", "model": "claude-sonnet-4-20250514", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01RkQY5ABrHjCsXPFdmETkwW", "name": "extract_structured_data", "input": {"metadata": {"letter_title": null, "send_date": ["1926-08-12"], "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft"], "receiver_persons": ["Dr. Max Vischer"]}}}], "stop_reason": "tool_use", "usage": {"input_tokens": 3834, "output_tokens": 99}}, "usage": {"input_tokens": 3834, "output_tokens": 99, "total_tokens": 3933}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.23, "f1_micro": 0.27, "cost_summary": {"total_input_tokens": 57250, "total_output_tokens": 2598, "total_tokens": 59848, "input_cost_usd": 0.17175, "output_cost_usd": 0.03897, "total_cost_usd": 0.21072, "pricing_date": "2025-09-30", "input_price_per_million": 3.0, "output_price_per_million": 15.0}}, "normalized_score": 23.0}, {"_id": {"$oid": "69d4eb12b877594bc5718938"}, "test_id": "T0073", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4.1-nano", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-4.1-nano", "duration": 1.5228817462921143, "timestamp": "2025-09-30T18:03:57.572414", "parsed": {"metadata": {"send_date": ["1926-03-26"], "letter_title": ["Letter to Herr Christ"], "sender_persons": ["K. L."], "receiver_persons": ["Herr Christ"]}}, "text": "", "raw_response": {"id": "chatcmpl-CLX7OWZtru4fNGWnlFNu8Bz5LLVO7", "model": "gpt-4.1-nano-2025-04-14", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\"metadata\":{\"send_date\":[\"1926-03-26\"],\"letter_title\":[\"Letter to Herr Christ\"],\"sender_persons\":[\"K. L.\"],\"receiver_persons\":[\"Herr Christ\"]}}", "role": "assistant"}}], "usage": {"prompt_tokens": 2304, "completion_tokens": 41, "total_tokens": 2345}}, "usage": {"input_tokens": 2304, "output_tokens": 41, "total_tokens": 2345}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.49, "f1_micro": 0.49, "cost_summary": {"total_input_tokens": 205620, "total_output_tokens": 2935, "total_tokens": 208555, "input_cost_usd": 0.020562, "output_cost_usd": 0.001174, "total_cost_usd": 0.021736, "pricing_date": "2025-09-30", "input_price_per_million": 0.1, "output_price_per_million": 0.4}}, "normalized_score": 49.0}, {"_id": {"$oid": "69d4eb12b877594bc571893a"}, "test_id": "T0069", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4.1", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-4.1", "duration": 5.731719732284546, "timestamp": "2025-09-30T17:57:44.174309", "parsed": {"metadata": {"send_date": ["1932-10-07"], "letter_title": ["null"], "sender_persons": ["Basler Personenschiffahrtsgesellschaft", "Arthur H. Gysin"], "receiver_persons": ["Vorstandsmitglieder der Basler Personenschiffahrtsgesellschaft"]}}, "text": "", "raw_response": {"id": "chatcmpl-CLX1JJPgMqCx86I92cAQOfAGl4yUJ", "model": "gpt-4.1-2025-04-14", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\"1932-10-07\"],\n \"letter_title\": [ \"null\" ],\n \"sender_persons\": [\"Basler Personenschiffahrtsgesellschaft\", \"Arthur H. Gysin\"],\n \"receiver_persons\": [\"Vorstandsmitglieder der Basler Personenschiffahrtsgesellschaft\"]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 1257, "completion_tokens": 76, "total_tokens": 1333}}, "usage": {"input_tokens": 1257, "output_tokens": 76, "total_tokens": 1333}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.56, "f1_micro": 0.5, "cost_summary": {"total_input_tokens": 63939, "total_output_tokens": 2097, "total_tokens": 66036, "input_cost_usd": 0.127878, "output_cost_usd": 0.016776, "total_cost_usd": 0.144654, "pricing_date": "2025-09-30", "input_price_per_million": 2.0, "output_price_per_million": 8.0}}, "normalized_score": 56.00000000000001}, {"_id": {"$oid": "69d4eb12b877594bc571893c"}, "test_id": "T0110", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-5", "duration": 51.25435972213745, "timestamp": "2025-09-30T21:07:17.478328", "parsed": {"metadata": {"send_date": ["1926-06-22"], "letter_title": ["null"], "sender_persons": ["null"], "receiver_persons": ["P. Christ-Wackernagel"]}}, "text": "", "raw_response": {"id": "chatcmpl-CLZy66w0jXRqDeDsg9LTL5XWxkXXN", "model": "gpt-5-2025-08-07", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\"metadata\":{\"send_date\":[\"1926-06-22\"],\"letter_title\":[\"null\"],\"sender_persons\":[\"null\"],\"receiver_persons\":[\"P. Christ-Wackernagel\"]}}", "role": "assistant"}}], "usage": {"prompt_tokens": 1118, "completion_tokens": 1845, "total_tokens": 2963}}, "usage": {"input_tokens": 1118, "output_tokens": 1845, "total_tokens": 2963}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.68, "f1_micro": 0.67, "cost_summary": {"total_input_tokens": 55306, "total_output_tokens": 69596, "total_tokens": 124902, "input_cost_usd": 0.069132, "output_cost_usd": 0.69596, "total_cost_usd": 0.765093, "pricing_date": "2025-09-30", "input_price_per_million": 1.25, "output_price_per_million": 10.0}}, "normalized_score": 68.0}, {"_id": {"$oid": "69d4eb12b877594bc571893d"}, "test_id": "T0072", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-4.1-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-4.1-mini", "duration": 3.3743813037872314, "timestamp": "2025-09-30T18:03:15.881224", "parsed": {"metadata": {"send_date": ["1932-09-07"], "letter_title": ["Betr.Personenschifffahrt"], "sender_persons": ["Basler Rheinschiffahrt Aktiengesellschaft"], "receiver_persons": ["Dr. M. Vischer-von Planta"]}}, "text": "", "raw_response": {"id": "chatcmpl-CLX6iPTyh6RL75h825RD0q2k9zfJK", "model": "gpt-4.1-mini-2025-04-14", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\"metadata\":{\"send_date\":[\"1932-09-07\"],\"letter_title\":[\"Betr.Personenschifffahrt\"],\"sender_persons\":[\"Basler Rheinschiffahrt Aktiengesellschaft\"],\"receiver_persons\":[\"Dr. M. Vischer-von Planta\"]}}", "role": "assistant"}}], "usage": {"prompt_tokens": 4074, "completion_tokens": 56, "total_tokens": 4130}}, "usage": {"input_tokens": 4074, "output_tokens": 56, "total_tokens": 4130}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.6, "f1_micro": 0.54, "cost_summary": {"total_input_tokens": 90966, "total_output_tokens": 1790, "total_tokens": 92756, "input_cost_usd": 0.036386, "output_cost_usd": 0.002864, "total_cost_usd": 0.03925, "pricing_date": "2025-09-30", "input_price_per_million": 0.4, "output_price_per_million": 1.6}}, "normalized_score": 60.0}, {"_id": {"$oid": "69d4eb12b877594bc571893f"}, "test_id": "T0112", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "openai", "model": "gpt-5-mini", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": true, \"skip_non_signatures\": false}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "openai", "model": "gpt-5-mini", "duration": 17.79159712791443, "timestamp": "2025-09-30T21:51:30.784163", "parsed": {"metadata": {"send_date": ["1926-08-13"], "letter_title": null, "sender_persons": ["Basler Rheinschiffahrt-Aktiengesellschaft", "Groschopf", "J. A. Ritter"], "receiver_persons": ["Dr. Max Vischer"]}}, "text": "", "raw_response": {"id": "chatcmpl-CLafS0e5hFf96s8gf61QvZkvtTUPM", "model": "gpt-5-mini-2025-08-07", "choices": [{"finish_reason": "stop", "index": 0, "message": {"content": "{\n \"metadata\": {\n \"send_date\": [\n \"1926-08-13\"\n ],\n \"letter_title\": null,\n \"sender_persons\": [\n \"Basler Rheinschiffahrt-Aktiengesellschaft\",\n \"Groschopf\",\n \"J. A. Ritter\"\n ],\n \"receiver_persons\": [\n \"Dr. Max Vischer\"\n ]\n }\n}", "role": "assistant"}}], "usage": {"prompt_tokens": 3143, "completion_tokens": 1124, "total_tokens": 4267}}, "usage": {"input_tokens": 3143, "output_tokens": 1124, "total_tokens": 4267}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.49, "f1_micro": 0.58, "cost_summary": {"total_input_tokens": 43175, "total_output_tokens": 25683, "total_tokens": 68858, "input_cost_usd": 0.010794, "output_cost_usd": 0.051366, "total_cost_usd": 0.06216, "pricing_date": "2025-09-30", "input_price_per_million": 0.25, "output_price_per_million": 2.0}}, "normalized_score": 49.0}, {"_id": {"$oid": "69d4eb12b877594bc5718940"}, "test_id": "T0057", "benchmark": "business_letters", "date": "2025-09-30", "tags": {"document-type": ["letter"], "writing": ["typed", "handwritten"], "century": [20], "language": ["de"], "layout": ["prose"], "entry-type": ["person", "location"], "task": ["information-extraction"]}, "contributors": ["eric_decker", "maximilian_hindermann", "lea_kasper", "anthea_alberto", "pema_frick", "jose_luis_losada_palenzuela", "sorin_marti", "elena_spadini"], "hidden": false, "config": {"provider": "genai", "model": "gemini-2.0-flash-lite", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge and an expert in the field of 20th century Swiss history", "prompt_file": "prompt.txt", "rules": "{\"skip_signatures\": false, \"skip_non_signatures\": true}", "legacy_test": false}, "prompt": " IDENTITY and PURPOSE:\n\n You are presented with a series of images constituting a historical letter. Your task is to extract the\n values of the following keys from the letter and return them in a JSON file where the values\n corresponding to each key should be stored as a list, even if there is only a single value for a\n key:\n\n - letter_title: Title of the letter.\n - sender_persons: Name(s) of the person(s) who wrote the letter.\n - send_date: The exact or approximate date the letter was written.\n - receiver_persons: Name(s) of the person(s) who received the letter.\n\n Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims\n and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for\n dates. If a piece of information is not included in the letter, set the value for the corresponding key\n to \"null\". Do not return anything except the JSON file.\n\n EXAMPLE:\n\n {\n \"letter_title\": [\"Petition for Environmental Protection\"],\n \"send_date\": [\"1993-03-12\"],\n \"sender_persons\": [\"Lisa Simpson\"],\n \"receiver_persons\": [\"Mayor Joe Quimby\", \"Seymour Skinner\"],\n }\n\n OUTPUT:", "results": {"provider": "genai", "model": "gemini-2.0-flash-lite", "duration": 1.5762560367584229, "timestamp": "2025-09-30T15:21:58.906905", "parsed": {"metadata": {"send_date": ["1928-09-28"], "letter_title": ["null"], "sender_persons": ["Verein f\u00fcr die Schiffahrt auf dem Oberrhein"], "receiver_persons": ["Dr. Max Vischer"]}}, "text": "{\n \"metadata\": {\n \"send_date\": [\n \"1928-09-28\"\n ],\n \"letter_title\": [\n \"null\"\n ],\n \"sender_persons\": [\n \"Verein f\u00fcr die Schiffahrt auf dem Oberrhein\"\n ],\n \"receiver_persons\": [\n \"Dr. Max Vischer\"\n ]\n }\n}", "raw_response": {"text": "{\n \"metadata\": {\n \"send_date\": [\n \"1928-09-28\"\n ],\n \"letter_title\": [\n \"null\"\n ],\n \"sender_persons\": [\n \"Verein f\u00fcr die Schiffahrt auf dem Oberrhein\"\n ],\n \"receiver_persons\": [\n \"Dr. Max Vischer\"\n ]\n }\n}", "usage_metadata": {"prompt_token_count": 2168, "candidates_token_count": 98, "total_token_count": 2266}}, "usage": {"input_tokens": 2168, "output_tokens": 98, "total_tokens": 2266}, "finish_reason": "stop"}, "scoring": {"f1_macro": 0.55, "f1_micro": 0.53, "cost_summary": {"total_input_tokens": 51058, "total_output_tokens": 3025, "total_tokens": 54083, "input_cost_usd": 0.003829, "output_cost_usd": 0.000907, "total_cost_usd": 0.004737, "pricing_date": "2025-09-30", "input_price_per_million": 0.075, "output_price_per_million": 0.3}}, "normalized_score": 55.00000000000001}]