{"_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}