{"_id": {"$oid": "6aa7a68ebf5ce6c3c2c5758d"}, "test_id": "T1755", "benchmark": "library_cards", "date": "2026-09-08", "tags": {"document-type": ["index-card"], "writing": ["typed", "printed", "handwritten"], "century": [20, 19], "language": ["de", "fr", "en", "la", "el", "fi", "sv", "pl"], "layout": ["index"], "entry-type": ["bibliographic"], "task": ["information-extraction"]}, "contributors": ["gabriel_muller", "maximilian_hindermann"], "hidden": false, "config": {"provider": "deepseek", "model": "deepseek-v4-flash-vision-exp", "dataclass": "Document", "temperature": 0.0, "role_description": "You are a historian with keyword knowledge", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": "Extract the bibliographic information about a historical dissertation from this index card and return it as a structured JSON object with the following exact format:\n\n```json\n{\n  \"type\": {\n    \"type\": \"Dissertation or thesis\" OR \"Reference\"\n  },\n  \"author\": {\n    \"last_name\": \"string\",\n    \"first_name\": \"string\"\n  },\n  \"publication\": {\n    \"title\": \"string\",\n    \"year\": integer,\n    \"place\": \"string or empty string\",\n    \"pages\": \"string or empty string\",\n    \"publisher\": \"string or empty string\",\n    \"format\": \"string or empty string\"\n  },\n  \"library_reference\": {\n    \"shelfmark\": \"string or empty string\",\n    \"subjects\": \"string or empty string\"\n  }\n}\n```\n\nEXTRACTION RULES:\n1. **Card Type**: If a card contains the note \"s.\" on a separate line, it is a \"Reference\". Otherwise, it is a \"Dissertation or thesis\".\n\n2. **Author**: Extract last_name and first_name. If only one name is given, put it in last_name and leave first_name empty.\n\n3. **Publication**:\n   - title: The main title of the work\n   - year: Publication year as integer\n   - place: Publication place\n   - pages: Page count (remove \" S.\" suffix if present)\n   - publisher: Publishing house/institution\n   - format: Usually \"8\u00b0\", \"8'\", or \"4\u00b0\" - single value only\n\n4. **Library Reference**:\n   - shelfmark: Often begins with \"Diss.\" or \"AT\", may be marked with \"Standort:\"\n   - subjects: Subject classifications or keywords\n\n5. **Missing Information**: Use empty string \"\" for missing text fields, omit year fields entirely if not present.\n\n6. **Ignore**: Disregard any information that doesn't fit into these categories.\n\nReturn ONLY the JSON object, no additional text or explanation.", "results": {"text": "{\"type\":{\"type\":\"Reference\"},\"author\":{\"last_name\":\"Montaghemi\",\"first_name\":\"Nourhomadeh\"},\"publication\":{\"title\":\"\",\"year\":\"\",\"place\":\"\",\"pages\":\"\",\"publisher\":\"\",\"format\":\"\",\"editor\":null},\"library_reference\":{\"shelfmark\":\"\",\"subjects\":\"\"}}", "model": "deepseek-v4-flash-vision-exp", "provider": "deepseek", "finish_reason": "stop", "usage": {"input_tokens": 1651, "output_tokens": 1292, "total_tokens": 2943, "input_cost_usd": 0.00072644, "output_cost_usd": 0.0017054400000000001, "estimated_cost_usd": 0.00243188}, "duration": 12.485541820526123, "timestamp": "2026-09-08T09:56:12.067174", "parsed": {"type": {"type": "Reference"}, "author": {"last_name": "Montaghemi", "first_name": "Nourhomadeh"}, "publication": {"title": "", "year": "", "place": "", "pages": "", "publisher": "", "format": ""}, "library_reference": {"shelfmark": "", "subjects": ""}}, "conversation_id": "ada415d5-bfd0-4c4e-8e9b-6d5dad0a1c73", "score": {"f1_score": 0.33, "precision": 0.3333333333333333, "recall": 0.3333333333333333, "true_positives": 1, "false_positives": 2, "false_negatives": 2, "field_scores": {"publication.place": {"response": null, "ground_truth": null, "score": 1.0}, "author.last_name": {"response": "Montaghemi", "ground_truth": "Sonnenbichler", "score": 0.34782608695652173}, "publication.publisher": {"response": null, "ground_truth": null, "score": 1.0}, "type.type": {"response": "Reference", "ground_truth": "Reference", "score": 1.0}, "publication.pages": {"response": null, "ground_truth": null, "score": 1.0}, "author.first_name": {"response": "Nourhomadeh", "ground_truth": null, "score": 0.0}, "library_reference.shelfmark": {"response": null, "ground_truth": null, "score": 1.0}, "publication.format": {"response": null, "ground_truth": null, "score": 1.0}, "publication.year": {"response": null, "ground_truth": null, "score": 1.0}, "publication.editor": {"response": null, "ground_truth": null, "score": 1.0}, "library_reference.subjects": {"response": null, "ground_truth": null, "score": 1.0}, "publication.title": {"response": null, "ground_truth": "Montaghemi, Nourhomadeh", "score": 0.0}}, "total_fields": 12}, "raw_response": "{\"id\":\"bd0f2393-9adc-4ea5-a3d4-495e4bd21c2f\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\\"type\\\":{\\\"type\\\":\\\"Reference\\\"},\\\"author\\\":{\\\"last_name\\\":\\\"Montaghemi\\\",\\\"first_name\\\":\\\"Nourhomadeh\\\"},\\\"publication\\\":{\\\"title\\\":\\\"\\\",\\\"year\\\":\\\"\\\",\\\"place\\\":\\\"\\\",\\\"pages\\\":\\\"\\\",\\\"publisher\\\":\\\"\\\",\\\"format\\\":\\\"\\\"},\\\"library_reference\\\":{\\\"shelfmark\\\":\\\"\\\",\\\"subjects\\\":\\\"\\\"}}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"reasoning_content\":\"We need to extract bibliographic info from the card. The card shows:\\n\\n\\\"Montaghemi, Nourhomadeh\\\"\\n\\\"s.\\\"\\n\\\"Sonnenbichler - Montaghemi, Nourhomadeh\\\"\\n\\nInterpretation: The card seems to be a reference card with author \\\"Montaghemi, Nourhomadeh\\\" and a cross-reference \\\"s.\\\" (siehe, meaning see) to \\\"Sonnenbichler - Montaghemi, Nourhomadeh\\\". This is typical for a \\\"see\\\" reference card (Reference type). However, the card explicitly says \\\"s.\\\" on a separate line, so according to rule 1, it is a \\\"Reference\\\" type.\\n\\nAuthor: The main author is Montaghemi, Nourhomadeh. So last_name = \\\"Montaghemi\\\", first_name = \\\"Nourhomadeh\\\". But note that the second line \\\"Sonnenbichler - Montaghemi, Nourhomadeh\\\" might be a see also reference, but we only extract the main author from the first line.\\n\\nPublication: No title, year, place, etc. We leave them empty strings. But the year field is required in the schema? Actually the schema has \\\"year\\\" as required in publication. In the extraction rules, rule 5 says \\\"Missing Information: Use empty string \\\"\\\" for missing text fields, omit year fields entirely if not present.\\\" But the schema requires \\\"year\\\" to be present as a string? It says publication.year is type string, and required. So we must include it as empty string if missing.\\n\\nSimilarly, place, pages, publisher, format are not present so empty strings.\\n\\npublication.title: Also empty string since no title given.\\n\\nLibrary reference: shelfmark and subjects not present, so empty strings.\\n\\nThus JSON:\\n\\n{\\n  \\\"type\\\": {\\\"type\\\": \\\"Reference\\\"},\\n  \\\"author\\\": {\\\"last_name\\\": \\\"Montaghemi\\\", \\\"first_name\\\": \\\"Nourhomadeh\\\"},\\n  \\\"publication\\\": {\\n    \\\"title\\\": \\\"\\\",\\n    \\\"year\\\": \\\"\\\",\\n    \\\"place\\\": \\\"\\\",\\n    \\\"pages\\\": \\\"\\\",\\n    \\\"publisher\\\": \\\"\\\",\\n    \\\"format\\\": \\\"\\\"\\n  },\\n  \\\"library_reference\\\": {\\n    \\\"shelfmark\\\": \\\"\\\",\\n    \\\"subjects\\\": \\\"\\\"\\n  }\\n}\\n\\nCheck if the card has any other info? No. The \\\"s.\\\" is a note indicating reference. So output accordingly.\\n\\nBut wait: The instruction says \\\"If a card contains the note 's.' on a separate line, it is a 'Reference'. Otherwise, it is a 'Dissertation or thesis'.\\\" So we have \\\"s.\\\" on a line, so type is \\\"Reference\\\". Author is from the first line. Good.\\n\\nEnsure we follow the schema exactly. The schema includes an \\\"editor\\\" field in publication? But the example output format in the user's prompt does not include editor. Actually the user's exact format at the top:\\n\\n```json\\n{\\n  \\\"type\\\": {\\n    \\\"type\\\": \\\"Dissertation or thesis\\\" OR \\\"Reference\\\"\\n  },\\n  \\\"author\\\": {\\n    \\\"last_name\\\": \\\"string\\\",\\n    \\\"first_name\\\": \\\"string\\\"\\n  },\\n  \\\"publication\\\": {\\n    \\\"title\\\": \\\"string\\\",\\n    \\\"year\\\": integer,\\n    \\\"place\\\": \\\"string or empty string\\\",\\n    \\\"pages\\\": \\\"string or empty string\\\",\\n    \\\"publisher\\\": \\\"string or empty string\\\",\\n    \\\"format\\\": \\\"string or empty string\\\"\\n  },\\n  \\\"library_reference\\\": {\\n    \\\"shelfmark\\\": \\\"string or empty string\\\",\\n    \\\"subjects\\\": \\\"string or empty string\\\"\\n  }\\n}\\n```\\n\\nIt says year: integer, but then extraction rules say \\\"omit year fields entirely if not present\\\". But then the schema from the prompt (the JSON Schema) has publication.year as string and required. And the system says \\\"You MUST respond with valid JSON matching this exact schema\\\". So we must follow the exact schema, which requires publication.year to be present and be a string. So we set it to \\\"\\\" if missing.\\n\\nAlso note: The schema has an additional field \\\"editor\\\" in publication, but the top-level example doesn't have it. The schema says \\\"publication\\\": {\\\"editor\\\": {\\\"anyOf\\\": [{\\\"type\\\": \\\"string\\\"}, {\\\"type\\\": \\\"null\\\"}], \\\"default\\\": null}} but it's not required. The top-level example doesn't include editor. To be safe, we can include editor: null? The schema says it's optional. But the example doesn't have it. However, the schema is the definitive requirement. But the instruction says \\\"Reply with JSON object ONLY.\\\" and \\\"You MUST respond with valid JSON matching this exact schema\\\". So we should include all required fields and any optional fields? The schema doesn't require editor, so we can omit it. But it's better to include it as null? Actually the schema defines editor as optional with default null, so omitting is fine. But to be consistent with the example, we can omit. However, the example in the user's prompt doesn't have editor, so we'll omit it.\\n\\nBut wait, the schema's \\\"publication\\\" requires \\\"title\\\" and \\\"year\\\". The schema says publication properties include editor, but not required. So we include title and year as empty strings. Good.\\n\\nAlso note: The schema says \\\"library_reference\\\" has shelfmark and subjects, both optional with default null. But the top-level example has them as strings or empty strings. So we'll put empty strings.\\n\\nThus the final JSON matches the schema.\\n\\nOne more nuance: The card says \\\"Montaghemi, Nourhomadeh\\\" - that's last name first, then first name. So indeed last_name = \\\"Montaghemi\\\", first_name = \\\"Nourhomadeh\\\". The second line is \\\"Sonnenbichler - Montaghemi, Nourhomadeh\\\" which is a see also reference, but we don't extract it.\\n\\nSo final output.\"}}],\"created\":1788854160,\"model\":\"deepseek-v4-flash-vision-exp\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":\"aa8d6caccae4a22492bb51091cfc8eab\",\"usage\":{\"completion_tokens\":1292,\"prompt_tokens\":1651,\"total_tokens\":2943,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":null,\"reasoning_tokens\":1226,\"rejected_prediction_tokens\":null},\"prompt_tokens_details\":{\"audio_tokens\":null,\"cached_tokens\":0},\"prompt_cache_hit_tokens\":0,\"prompt_cache_miss_tokens\":1651}}"}, "scoring": {"f1_micro": 0.8840639082343302, "f1_macro": 0.8797338403041826, "micro_precision": 0.8747466558573166, "micro_recall": 0.8935817805383023, "total_instances": 263, "total_tp": 2158, "total_fp": 309, "total_fn": 257, "cost_summary": {"total_input_tokens": 429709, "total_output_tokens": 523599, "total_tokens": 953308, "input_cost_usd": 0.18907196000000054, "output_cost_usd": 0.69115068, "total_cost_usd": 0.8802226400000008}}, "pricing": {"bucket_date": "2026-09-08", "age_days": 0, "input_price_per_million": 0.44, "output_price_per_million": 1.32}, "timing": {"total_response_s": 4906.12, "mean_response_s": 18.65, "slowest_response_s": 52.93, "inputs_timed": 263, "inputs_stored": 263, "span_s": 487.65}, "normalized_score": 87.97338403041826}