{"_id": {"$oid": "6a1010f996d87b97b14cf8c8"}, "test_id": "T0903", "benchmark": "personnel_cards", "date": "2026-04-21", "tags": {"document-type": ["index-card"], "writing": ["handwritten", "typed", "printed"], "century": [20], "layout": ["table", "form"], "task": ["transcription", "document-understanding", "data-correction"], "language": ["de", "fr"]}, "contributors": ["tabea_wullschleger", "maximilian_hindermann"], "hidden": false, "config": {"provider": "openrouter", "model": "qwen/qwen3.6-plus", "dataclass": "Table", "temperature": 0.0, "role_description": "You are a historian specializing in 20th century personnel records and administrative documents", "prompt_file": "prompt.txt", "legacy_test": false}, "prompt": "Extract all information from this personnel card table and return it as a structured JSON object. The card contains rows documenting employment history with positions, locations, salary information, dates, and remarks.\n\nREQUIRED JSON STRUCTURE:\n```json\n{\n  \"rows\": [\n    {\n      \"row_number\": 1,\n      \"dienstliche_stellung\": {\n        \"diplomatic_transcript\": \"exact text from card\",\n        \"interpretation\": \"expanded/standardized form or null\",\n        \"is_crossed_out\": false\n      },\n      \"dienstort\": {\n        \"diplomatic_transcript\": \"exact text from card\",\n        \"interpretation\": \"expanded/standardized form or null\",\n        \"is_crossed_out\": false\n      },\n      \"gehaltsklasse\": {\n        \"diplomatic_transcript\": \"exact text from card\",\n        \"interpretation\": \"expanded/standardized form or null\",\n        \"is_crossed_out\": false\n      },\n      \"jahresgehalt_monatsgehalt_taglohn\": {\n        \"diplomatic_transcript\": \"exact text from card\",\n        \"interpretation\": \"standardized numeric form or null\",\n        \"is_crossed_out\": false\n      },\n      \"datum_gehalts\u00e4nderung\": {\n        \"diplomatic_transcript\": \"exact text from card\",\n        \"interpretation\": \"YYYY-MM-DD format or null\",\n        \"is_crossed_out\": false\n      },\n      \"bemerkungen\": {\n        \"diplomatic_transcript\": \"exact text from card\",\n        \"interpretation\": \"expanded/standardized form or null\",\n        \"is_crossed_out\": false\n      }\n    }\n  ]\n}\n```\n\nCOLUMN DEFINITIONS:\n1. **dienstliche_stellung**: Official position or job title (e.g., \"Assistent\", \"Professor\", \"Sekret\u00e4r\")\n2. **dienstort**: Place of service or work location (e.g., \"Basel\", \"Z\u00fcrich\")\n3. **gehaltsklasse**: Salary class or grade (e.g., \"III\", \"IV\", roman numerals or numbers)\n4. **jahresgehalt_monatsgehalt_taglohn**: Salary amount (annual/monthly/daily wage)\n5. **datum_gehalts\u00e4nderung**: Date of salary change or effective date\n6. **bemerkungen**: Remarks, notes, or additional comments\n\nFIELD EXTRACTION RULES:\n\n**diplomatic_transcript** (REQUIRED for all fields):\n- Transcribe EXACTLY as written on the card\n- Include all abbreviations, punctuation, and formatting as they appear\n- Preserve original capitalization and spacing\n- Include currency symbols and separators (e.g., \"Fr. 2'400.-\", \"3.700.-\")\n- For dates, copy the exact format (e.g., \"1. Jan. 1946\", \"1.April 1945\")\n- Use empty string \"\" for empty cells\n- Be sure to escape ditto marks (repetition marks such as `\"` indicating \"same as above\")\n- DO NOT expand abbreviations or standardize formats\n- Do not transcribe checkmarks\n\n**interpretation** (OPTIONAL - use null if not applicable):\n- For ditto marks (repetition marks such as `\"`): Replace with the actual repeated value from the previous row in the same column\n  - For example, if previous row's dienstliche_stellung is \"Hilfsleiterin\" and current row has `\"`, interpret as \"Hilfsleiterin\"\n  - Do NOT add explanatory text like \"wie oben\" or similar - just provide the repeated value\n- Never expand abbreviations\n- For dates: Convert to ISO format YYYY-MM-DD\n  - \"1. Jan. 1946\" \u2192 \"1946-01-01\"\n  - \"1.April 1945\" \u2192 \"1945-04-01\"\n- For salary amounts: Extract numeric value only (remove currency symbols, separators)\n  - \"Fr. 2'400.-\" \u2192 \"2400\"\n  - \"3.700.-\" \u2192 \"3700\"\n  - \"5.094.-\" \u2192 \"5094\"\n  \"6,30.-\" \u2192 \"6.3\"\n- For salary class: Convert roman numerals to arabic if clear\n  - \"III\" \u2192 \"3\"\n  - \"IV\" \u2192 \"4\"\n- Do not convert roman numerals to arabic if not salary, date, or salary class\n- Use null if no interpretation/expansion is needed or if the field is empty\n- \"+ {word}\" where {word} is a word does not need interpretation\n\n**is_crossed_out** (REQUIRED for all fields):\n- Set to true if text in this field is crossed out, struck through, or deleted\n- Set to false if text is normal (not crossed out)\n- Empty cells should have is_crossed_out: false\n\nROW HANDLING:\n- Number rows sequentially starting from 1 (top to bottom)\n- Include ALL rows that have ANY content in ANY column\n- Empty rows (all cells empty) should be omitted\n- A row with only one filled cell should still be included\n\nIMPORTANT NOTES:\n- Return ONLY the JSON object, no additional text or explanation\n- Every field must have all three sub-fields: diplomatic_transcript, interpretation, is_crossed_out\n- diplomatic_transcript must never be null (use empty string \"\" for empty cells)\n- interpretation can be null when no expansion/standardization applies\n- Process the entire table from top to bottom\n- Maintain consistent row numbering throughout\n", "results": {"text": "{\"rows\":[{\"row_number\":1,\"dienstliche_stellung\":{\"diplomatic_transcript\":\"Hilfsleiterin\",\"interpretation\":null,\"is_crossed_out\":false},\"dienstort\":{\"diplomatic_transcript\":\"\",\"interpretation\":null,\"is_crossed_out\":false},\"gehaltsklasse\":{\"diplomatic_transcript\":\"\",\"interpretation\":null,\"is_crossed_out\":false},\"jahresgehalt_monatsgehalt_taglohn\":{\"diplomatic_transcript\":\"3500.-\",\"interpretation\":\"3500\",\"is_crossed_out\":false},\"datum_gehalts\u00e4nderung\":{\"diplomatic_transcript\":\"21. Jan. 46\",\"interpretation\":\"1946-01-21\",\"is_crossed_out\":false},\"bemerkungen\":{\"diplomatic_transcript\":\"+ Zulagen\",\"interpretation\":null,\"is_crossed_out\":false}}]}", "model": "qwen/qwen3.6-plus-04-02", "provider": "openrouter", "finish_reason": "stop", "usage": {"input_tokens": 5307, "output_tokens": 2071, "total_tokens": 7378, "input_cost_usd": 0.001724775, "output_cost_usd": 0.00403845, "estimated_cost_usd": 0.005763225}, "duration": 26.95997166633606, "timestamp": "2026-04-21T12:34:58.963471", "parsed": {"rows": [{"row_number": 1, "dienstliche_stellung": {"diplomatic_transcript": "Hilfsleiterin", "interpretation": null, "is_crossed_out": false}, "dienstort": {"diplomatic_transcript": "", "interpretation": null, "is_crossed_out": false}, "gehaltsklasse": {"diplomatic_transcript": "", "interpretation": null, "is_crossed_out": false}, "jahresgehalt_monatsgehalt_taglohn": {"diplomatic_transcript": "3500.-", "interpretation": "3500", "is_crossed_out": false}, "datum_gehalts\u00e4nderung": {"diplomatic_transcript": "21. Jan. 46", "interpretation": "1946-01-21", "is_crossed_out": false}, "bemerkungen": {"diplomatic_transcript": "+ Zulagen", "interpretation": null, "is_crossed_out": false}}]}, "conversation_id": "6e8d9c81-55f1-438f-83db-edc70d99fc65", "score": {"f1_score": 1.0, "precision": 1.0, "recall": 1.0, "true_positives": 12, "false_positives": 0, "false_negatives": 0, "field_scores": {"rows[0].bemerkungen.interpretation": {"response": null, "ground_truth": null, "score": 1.0}, "rows[0].dienstort.is_crossed_out": {"response": false, "ground_truth": false, "score": 1.0}, "rows[0].dienstliche_stellung.diplomatic_transcript": {"response": "Hilfsleiterin", "ground_truth": "Hilfsleiterin", "score": 1.0}, "rows[0].jahresgehalt_monatsgehalt_taglohn.is_crossed_out": {"response": false, "ground_truth": false, "score": 1.0}, "rows[0].datum_gehalts\u00e4nderung.diplomatic_transcript": {"response": "21. Jan. 46", "ground_truth": "21. Jan. 46", "score": 1.0}, "rows[0].bemerkungen.diplomatic_transcript": {"response": "+ Zulagen", "ground_truth": "+ Zulagen", "score": 1.0}, "rows[0].datum_gehalts\u00e4nderung.interpretation": {"response": "1946-01-21", "ground_truth": "1946-01-21", "score": 1.0}, "rows[0].dienstliche_stellung.interpretation": {"response": null, "ground_truth": null, "score": 1.0}, "rows[0].dienstort.diplomatic_transcript": {"response": null, "ground_truth": null, "score": 1.0}, "rows[0].bemerkungen.is_crossed_out": {"response": false, "ground_truth": false, "score": 1.0}, "rows[0].dienstort.interpretation": {"response": null, "ground_truth": null, "score": 1.0}, "rows[0].jahresgehalt_monatsgehalt_taglohn.diplomatic_transcript": {"response": "3500.-", "ground_truth": "3500.-", "score": 1.0}, "rows[0].dienstliche_stellung.is_crossed_out": {"response": false, "ground_truth": false, "score": 1.0}, "rows[0].jahresgehalt_monatsgehalt_taglohn.interpretation": {"response": "3500", "ground_truth": "3500", "score": 1.0}, "rows[0].gehaltsklasse.is_crossed_out": {"response": false, "ground_truth": false, "score": 1.0}, "rows[0].datum_gehalts\u00e4nderung.is_crossed_out": {"response": false, "ground_truth": false, "score": 1.0}, "rows[0].gehaltsklasse.interpretation": {"response": null, "ground_truth": null, "score": 1.0}, "rows[0].gehaltsklasse.diplomatic_transcript": {"response": null, "ground_truth": null, "score": 1.0}}, "total_fields": 19}, "raw_response": "{\"id\":\"gen-1776767672-3rZQEAJz6AcwTFEinpuj\",\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"{\\n  \\\"rows\\\": [\\n    {\\n      \\\"row_number\\\": 1,\\n      \\\"dienstliche_stellung\\\": {\\n        \\\"diplomatic_transcript\\\": \\\"Hilfsleiterin\\\",\\n        \\\"interpretation\\\": null,\\n        \\\"is_crossed_out\\\": false\\n      },\\n      \\\"dienstort\\\": {\\n        \\\"diplomatic_transcript\\\": \\\"\\\",\\n        \\\"interpretation\\\": null,\\n        \\\"is_crossed_out\\\": false\\n      },\\n      \\\"gehaltsklasse\\\": {\\n        \\\"diplomatic_transcript\\\": \\\"\\\",\\n        \\\"interpretation\\\": null,\\n        \\\"is_crossed_out\\\": false\\n      },\\n      \\\"jahresgehalt_monatsgehalt_taglohn\\\": {\\n        \\\"diplomatic_transcript\\\": \\\"3500.-\\\",\\n        \\\"interpretation\\\": \\\"3500\\\",\\n        \\\"is_crossed_out\\\": false\\n      },\\n      \\\"datum_gehalts\u00e4nderung\\\": {\\n        \\\"diplomatic_transcript\\\": \\\"21. Jan. 46\\\",\\n        \\\"interpretation\\\": \\\"1946-01-21\\\",\\n        \\\"is_crossed_out\\\": false\\n      },\\n      \\\"bemerkungen\\\": {\\n        \\\"diplomatic_transcript\\\": \\\"+ Zulagen\\\",\\n        \\\"interpretation\\\": null,\\n        \\\"is_crossed_out\\\": false\\n      }\\n    }\\n  ]\\n}\",\"refusal\":null,\"role\":\"assistant\",\"annotations\":null,\"audio\":null,\"function_call\":null,\"tool_calls\":null,\"parsed\":{\"rows\":[{\"row_number\":1,\"dienstliche_stellung\":{\"diplomatic_transcript\":\"Hilfsleiterin\",\"interpretation\":null,\"is_crossed_out\":false},\"dienstort\":{\"diplomatic_transcript\":\"\",\"interpretation\":null,\"is_crossed_out\":false},\"gehaltsklasse\":{\"diplomatic_transcript\":\"\",\"interpretation\":null,\"is_crossed_out\":false},\"jahresgehalt_monatsgehalt_taglohn\":{\"diplomatic_transcript\":\"3500.-\",\"interpretation\":\"3500\",\"is_crossed_out\":false},\"datum_gehalts\u00e4nderung\":{\"diplomatic_transcript\":\"21. Jan. 46\",\"interpretation\":\"1946-01-21\",\"is_crossed_out\":false},\"bemerkungen\":{\"diplomatic_transcript\":\"+ Zulagen\",\"interpretation\":null,\"is_crossed_out\":false}}]},\"reasoning\":\"user wants me to extract information from a personnel card image and format it as a JSON object.\\n\\n**1. Analyze the image:**\\n- The image shows a table with headers:\\n    - \\\"Dienstliche Stellung\\\" (Official Position)\\n    - \\\"Dienstort\\\" (Place of Service)\\n    - \\\"Gehaltsklasse\\\" (Salary Class)\\n    - \\\"Jahresgehalt Monatsgehalt Taglohn\\\" (Annual Salary / Monthly Salary / Daily Wage)\\n    - \\\"Zeitpunkt der Gehalts\u00e4nderung\\\" (Date of Salary Change) split into \\\"Tag\\\" (Day), \\\"Monat\\\" (Month), \\\"Jahr\\\" (Year)\\n    - \\\"Bemerkungen, Akten etc.\\\" (Remarks, Files etc.)\\n\\n- There is one row of data visible.\\n    - **Dienstliche Stellung:** \\\"Hilfsleiterin\\\"\\n    - **Dienstort:** Empty\\n    - **Gehaltsklasse:** There is a checkmark (\u2713). The instructions say \\\"Do not transcribe checkmarks\\\". So this should be an empty string \\\"\\\".\\n    - **Jahresgehalt...:** \\\"3500.-\\\"\\n    - **Zeitpunkt der Gehalts\u00e4nderung:**\\n        - Tag: \\\"21.\\\"\\n        - Monat: \\\"Jan.\\\"\\n        - Jahr: \\\"46\\\"\\n        - Combined for diplomatic transcript: \\\"21. Jan. 46\\\" (Wait, the columns are separate. I need to combine them into one field `datum_gehalts\u00e4nderung` based on the schema. The schema has one field for the date. I should combine the parts: \\\"21. Jan. 46\\\").\\n    - **Bemerkungen:** \\\"+ Zulagen\\\"\\n\\n**2. Map to JSON structure:**\\n\\n*   **Row 1:**\\n    *   `dienstliche_stellung`:\\n        *   `diplomatic_transcript`: \\\"Hilfsleiterin\\\"\\n        *   `interpretation`: null (It's a standard German word, no abbreviation to expand really, though \\\"Hilfsleiterin\\\" means Assistant Manager/Director. The instructions say \\\"Never expand abbreviations\\\" but also \\\"interpretation... expanded/standardized form\\\". \\\"Hilfsleiterin\\\" is already the full word. I'll leave it null or maybe just the word itself if it's considered an interpretation? No, usually interpretation is for abbreviations like \\\"Prof.\\\" -> \\\"Professor\\\". Here it's full text. So null is safer, or just repeat the text if it's a standard form. Let's look at the example: \\\"Assistent\\\" -> \\\"Assistent\\\". Wait, the example says \\\"interpretation\\\": \\\"expanded/standardized form or null\\\". If the text is already standard, null is appropriate unless there's a specific reason. Let's stick to null for full words unless they are abbreviations.) Actually, looking at the prompt's example: `\\\"interpretation\\\": \\\"expanded/standardized form or null\\\"`. If the text is \\\"Hilfsleiterin\\\", the interpretation is just \\\"Hilfsleiterin\\\" or null. Let's assume null if no expansion is needed.\\n    *   `dienstort`:\\n        *   `diplomatic_transcript`: \\\"\\\"\\n        *   `interpretation`: null\\n    *   `gehaltsklasse`:\\n        *   `diplomatic_transcript`: \\\"\\\" (The checkmark is not text).\\n        *   `interpretation`: null\\n    *   `jahresgehalt_monatsgehalt_taglohn`:\\n        *   `diplomatic_transcript`: \\\"3500.-\\\"\\n        *   `interpretation`: \\\"3500\\\" (Remove currency symbols/separators).\\n    *   `datum_gehalts\u00e4nderung`:\\n        *   `diplomatic_transcript`: \\\"21. Jan. 46\\\" (Combining the three sub-columns).\\n        *   `interpretation`: \\\"1946-01-21\\\" (ISO format).\\n    *   `bemerkungen`:\\n        *   `diplomatic_transcript`: \\\"+ Zulagen\\\"\\n        *   `interpretation`: null (The prompt says \\\"+ {word} where {word} is a word does not need interpretation\\\").\\n\\n**3. Refine the extraction:**\\n\\n*   **Row 1:**\\n    *   `dienstliche_stellung`: \\\"Hilfsleiterin\\\"\\n    *   `dienstort`: \\\"\\\"\\n    *   `gehaltsklasse`: \\\"\\\" (Checkmark ignored)\\n    *   `jahresgehalt...`: \\\"3500.-\\\" -> interpretation \\\"3500\\\"\\n    *   `datum...`: \\\"21. Jan. 46\\\" -> interpretation \\\"1946-01-21\\\"\\n    *   `bemerkungen`: \\\"+ Zulagen\\\" -> interpretation null.\\n\\nLet's double check the `gehaltsklasse` column. There is a checkmark. The instructions say \\\"Do not transcribe checkmarks\\\". So `diplomatic_transcript` is \\\"\\\".\\n\\nLet's double check the date. The columns are \\\"Tag\\\", \\\"Monat\\\", \\\"Jahr\\\".\\nTag: \\\"21.\\\"\\nMonat: \\\"Jan.\\\"\\nJahr: \\\"46\\\"\\nSo `diplomatic_transcript` for `datum_gehalts\u00e4nderung` should be \\\"21. Jan. 46\\\".\\n`interpretation`: \\\"1946-01-21\\\".\\n\\nLet's double check `jahresgehalt...`.\\nText: \\\"3500.-\\\"\\n`interpretation`: \\\"3500\\\".\\n\\nLet's double check `bemerkungen`.\\nText: \\\"+ Zulagen\\\"\\n`interpretation`: null (per rule \\\"+ {word} ... does not need interpretation\\\").\\n\\n**4. Final JSON construction:**\\n\\n```json\\n{\\n  \\\"rows\\\": [\\n    {\\n      \\\"row_number\\\": 1,\\n      \\\"dienstliche_stellung\\\": {\\n        \\\"diplomatic_transcript\\\": \\\"Hilfsleiterin\\\",\\n        \\\"interpretation\\\": null,\\n        \\\"is_crossed_out\\\": false\\n      },\\n      \\\"dienstort\\\": {\\n        \\\"diplomatic_transcript\\\": \\\"\\\",\\n        \\\"interpretation\\\": null,\\n        \\\"is_crossed_out\\\": false\\n      },\\n      \\\"gehaltsklasse\\\": {\\n        \\\"diplomatic_transcript\\\": \\\"\\\",\\n        \\\"interpretation\\\": null,\\n        \\\"is_crossed_out\\\": false\\n      },\\n      \\\"jahresgehalt_monatsgehalt_taglohn\\\": {\\n        \\\"diplomatic_transcript\\\": \\\"3500.-\\\",\\n        \\\"interpretation\\\": \\\"3500\\\",\\n        \\\"is_crossed_out\\\": false\\n      },\\n      \\\"datum_gehalts\u00e4nderung\\\": {\\n        \\\"diplomatic_transcript\\\": \\\"21. Jan. 46\\\",\\n        \\\"interpretation\\\": \\\"1946-01-21\\\",\\n        \\\"is_crossed_out\\\": false\\n      },\\n      \\\"bemerkungen\\\": {\\n        \\\"diplomatic_transcript\\\": \\\"+ Zulagen\\\",\\n        \\\"interpretation\\\": null,\\n        \\\"is_crossed_out\\\": false\\n      }\\n    }\\n  ]\\n}\\n```\\nWait, looking closer at the `gehaltsklasse` column. It has a checkmark. Is it possible the checkmark implies something? Usually, it might mean \\\"see remarks\\\" or just \\\"approved\\\". But the instruction is explicit: \\\"Do not transcribe checkmarks\\\". So empty string is correct.\\n\\nOne detail: `datum_gehalts\u00e4nderung`. The header is split into Tag, Monat, Jahr. The data is \\\"21.\\\", \\\"Jan.\\\", \\\"46\\\".\\nSo `diplomatic_transcript` should probably combine them with spaces: \\\"21. Jan. 46\\\".\\n\\nOne detail: `jahresgehalt_monatsgehalt_taglohn`. The text is \\\"3500.-\\\".\\nInterpretation: \\\"3500\\\".\\n\\nOne detail: `dienstliche_stellung`. \\\"Hilfsleiterin\\\".\\nInterpretation: null.\\n\\nOne detail: `bemerkungen`. \\\"+ Zulagen\\\".\\nInterpretation: null.\\n\\nThe plan looks solid.\",\"reasoning_details\":[{\"type\":\"reasoning.text\",\"text\":\"user wants me to extract information from a personnel card image and format it as a JSON object.\\n\\n**1. Analyze the image:**\\n- The image shows a table with headers:\\n    - \\\"Dienstliche Stellung\\\" (Official Position)\\n    - \\\"Dienstort\\\" (Place of Service)\\n    - \\\"Gehaltsklasse\\\" (Salary Class)\\n    - \\\"Jahresgehalt Monatsgehalt Taglohn\\\" (Annual Salary / Monthly Salary / Daily Wage)\\n    - \\\"Zeitpunkt der Gehalts\u00e4nderung\\\" (Date of Salary Change) split into \\\"Tag\\\" (Day), \\\"Monat\\\" (Month), \\\"Jahr\\\" (Year)\\n    - \\\"Bemerkungen, Akten etc.\\\" (Remarks, Files etc.)\\n\\n- There is one row of data visible.\\n    - **Dienstliche Stellung:** \\\"Hilfsleiterin\\\"\\n    - **Dienstort:** Empty\\n    - **Gehaltsklasse:** There is a checkmark (\u2713). The instructions say \\\"Do not transcribe checkmarks\\\". So this should be an empty string \\\"\\\".\\n    - **Jahresgehalt...:** \\\"3500.-\\\"\\n    - **Zeitpunkt der Gehalts\u00e4nderung:**\\n        - Tag: \\\"21.\\\"\\n        - Monat: \\\"Jan.\\\"\\n        - Jahr: \\\"46\\\"\\n        - Combined for diplomatic transcript: \\\"21. Jan. 46\\\" (Wait, the columns are separate. I need to combine them into one field `datum_gehalts\u00e4nderung` based on the schema. The schema has one field for the date. I should combine the parts: \\\"21. Jan. 46\\\").\\n    - **Bemerkungen:** \\\"+ Zulagen\\\"\\n\\n**2. Map to JSON structure:**\\n\\n*   **Row 1:**\\n    *   `dienstliche_stellung`:\\n        *   `diplomatic_transcript`: \\\"Hilfsleiterin\\\"\\n        *   `interpretation`: null (It's a standard German word, no abbreviation to expand really, though \\\"Hilfsleiterin\\\" means Assistant Manager/Director. The instructions say \\\"Never expand abbreviations\\\" but also \\\"interpretation... expanded/standardized form\\\". \\\"Hilfsleiterin\\\" is already the full word. I'll leave it null or maybe just the word itself if it's considered an interpretation? No, usually interpretation is for abbreviations like \\\"Prof.\\\" -> \\\"Professor\\\". Here it's full text. So null is safer, or just repeat the text if it's a standard form. Let's look at the example: \\\"Assistent\\\" -> \\\"Assistent\\\". Wait, the example says \\\"interpretation\\\": \\\"expanded/standardized form or null\\\". If the text is already standard, null is appropriate unless there's a specific reason. Let's stick to null for full words unless they are abbreviations.) Actually, looking at the prompt's example: `\\\"interpretation\\\": \\\"expanded/standardized form or null\\\"`. If the text is \\\"Hilfsleiterin\\\", the interpretation is just \\\"Hilfsleiterin\\\" or null. Let's assume null if no expansion is needed.\\n    *   `dienstort`:\\n        *   `diplomatic_transcript`: \\\"\\\"\\n        *   `interpretation`: null\\n    *   `gehaltsklasse`:\\n        *   `diplomatic_transcript`: \\\"\\\" (The checkmark is not text).\\n        *   `interpretation`: null\\n    *   `jahresgehalt_monatsgehalt_taglohn`:\\n        *   `diplomatic_transcript`: \\\"3500.-\\\"\\n        *   `interpretation`: \\\"3500\\\" (Remove currency symbols/separators).\\n    *   `datum_gehalts\u00e4nderung`:\\n        *   `diplomatic_transcript`: \\\"21. Jan. 46\\\" (Combining the three sub-columns).\\n        *   `interpretation`: \\\"1946-01-21\\\" (ISO format).\\n    *   `bemerkungen`:\\n        *   `diplomatic_transcript`: \\\"+ Zulagen\\\"\\n        *   `interpretation`: null (The prompt says \\\"+ {word} where {word} is a word does not need interpretation\\\").\\n\\n**3. Refine the extraction:**\\n\\n*   **Row 1:**\\n    *   `dienstliche_stellung`: \\\"Hilfsleiterin\\\"\\n    *   `dienstort`: \\\"\\\"\\n    *   `gehaltsklasse`: \\\"\\\" (Checkmark ignored)\\n    *   `jahresgehalt...`: \\\"3500.-\\\" -> interpretation \\\"3500\\\"\\n    *   `datum...`: \\\"21. Jan. 46\\\" -> interpretation \\\"1946-01-21\\\"\\n    *   `bemerkungen`: \\\"+ Zulagen\\\" -> interpretation null.\\n\\nLet's double check the `gehaltsklasse` column. There is a checkmark. The instructions say \\\"Do not transcribe checkmarks\\\". So `diplomatic_transcript` is \\\"\\\".\\n\\nLet's double check the date. The columns are \\\"Tag\\\", \\\"Monat\\\", \\\"Jahr\\\".\\nTag: \\\"21.\\\"\\nMonat: \\\"Jan.\\\"\\nJahr: \\\"46\\\"\\nSo `diplomatic_transcript` for `datum_gehalts\u00e4nderung` should be \\\"21. Jan. 46\\\".\\n`interpretation`: \\\"1946-01-21\\\".\\n\\nLet's double check `jahresgehalt...`.\\nText: \\\"3500.-\\\"\\n`interpretation`: \\\"3500\\\".\\n\\nLet's double check `bemerkungen`.\\nText: \\\"+ Zulagen\\\"\\n`interpretation`: null (per rule \\\"+ {word} ... does not need interpretation\\\").\\n\\n**4. Final JSON construction:**\\n\\n```json\\n{\\n  \\\"rows\\\": [\\n    {\\n      \\\"row_number\\\": 1,\\n      \\\"dienstliche_stellung\\\": {\\n        \\\"diplomatic_transcript\\\": \\\"Hilfsleiterin\\\",\\n        \\\"interpretation\\\": null,\\n        \\\"is_crossed_out\\\": false\\n      },\\n      \\\"dienstort\\\": {\\n        \\\"diplomatic_transcript\\\": \\\"\\\",\\n        \\\"interpretation\\\": null,\\n        \\\"is_crossed_out\\\": false\\n      },\\n      \\\"gehaltsklasse\\\": {\\n        \\\"diplomatic_transcript\\\": \\\"\\\",\\n        \\\"interpretation\\\": null,\\n        \\\"is_crossed_out\\\": false\\n      },\\n      \\\"jahresgehalt_monatsgehalt_taglohn\\\": {\\n        \\\"diplomatic_transcript\\\": \\\"3500.-\\\",\\n        \\\"interpretation\\\": \\\"3500\\\",\\n        \\\"is_crossed_out\\\": false\\n      },\\n      \\\"datum_gehalts\u00e4nderung\\\": {\\n        \\\"diplomatic_transcript\\\": \\\"21. Jan. 46\\\",\\n        \\\"interpretation\\\": \\\"1946-01-21\\\",\\n        \\\"is_crossed_out\\\": false\\n      },\\n      \\\"bemerkungen\\\": {\\n        \\\"diplomatic_transcript\\\": \\\"+ Zulagen\\\",\\n        \\\"interpretation\\\": null,\\n        \\\"is_crossed_out\\\": false\\n      }\\n    }\\n  ]\\n}\\n```\\nWait, looking closer at the `gehaltsklasse` column. It has a checkmark. Is it possible the checkmark implies something? Usually, it might mean \\\"see remarks\\\" or just \\\"approved\\\". But the instruction is explicit: \\\"Do not transcribe checkmarks\\\". So empty string is correct.\\n\\nOne detail: `datum_gehalts\u00e4nderung`. The header is split into Tag, Monat, Jahr. The data is \\\"21.\\\", \\\"Jan.\\\", \\\"46\\\".\\nSo `diplomatic_transcript` should probably combine them with spaces: \\\"21. Jan. 46\\\".\\n\\nOne detail: `jahresgehalt_monatsgehalt_taglohn`. The text is \\\"3500.-\\\".\\nInterpretation: \\\"3500\\\".\\n\\nOne detail: `dienstliche_stellung`. \\\"Hilfsleiterin\\\".\\nInterpretation: null.\\n\\nOne detail: `bemerkungen`. \\\"+ Zulagen\\\".\\nInterpretation: null.\\n\\nThe plan looks solid.\",\"format\":\"unknown\",\"index\":0}]},\"native_finish_reason\":\"stop\"}],\"created\":1776767672,\"model\":\"qwen/qwen3.6-plus-04-02\",\"object\":\"chat.completion\",\"service_tier\":null,\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":2071,\"prompt_tokens\":5307,\"total_tokens\":7378,\"completion_tokens_details\":{\"accepted_prediction_tokens\":null,\"audio_tokens\":0,\"reasoning_tokens\":1760,\"rejected_prediction_tokens\":null,\"image_tokens\":0},\"prompt_tokens_details\":{\"audio_tokens\":0,\"cached_tokens\":0,\"cache_write_tokens\":0,\"video_tokens\":0},\"cost\":0.005763225,\"is_byok\":false,\"cost_details\":{\"upstream_inference_cost\":0.005763225,\"upstream_inference_prompt_cost\":0.001724775,\"upstream_inference_completions_cost\":0.00403845}},\"provider\":\"Alibaba\"}"}, "scoring": {"f1_micro": 0.960270162892332, "f1_macro": 0.8886885245901639, "micro_precision": 0.9606518282988871, "micro_recall": 0.9598888006354249, "total_instances": 61, "total_tp": 2417, "total_fp": 99, "total_fn": 101, "cost_summary": {"total_input_tokens": 320404, "total_output_tokens": 251085, "total_tokens": 571489, "input_cost_usd": 0.10413129999999994, "output_cost_usd": 0.48961575000000007, "total_cost_usd": 0.59374705}}, "normalized_score": 96.0270162892332}