RISE Humanities Data Benchmark, 0.5.0-pre1

Search Test Runs

 

A test run is a single execution of a benchmark test using a defined model configuration.
Each run represents how a particular large language model (LLM) — such as GPT-4, Claude-3, or Gemini — performed on a given task at a specific time, with specific settings.

A test run includes:

  • Prompt and role definition – what the model was asked to do and from what perspective (e.g. “as a historian”).
  • Model configuration – provider, model version, temperature, and other generation parameters.
  • Results – the model’s actual response and its evaluation (scores such as F1 or accuracy).
  • Usage and cost data – token counts and calculated API costs.
  • Metadata – information like the test date, benchmark name, and person who executed it.

Together, test runs make it possible to compare models, providers, and configurations across benchmarks in a transparent and reproducible way.

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Your search for Benchmark 'library_cards__true' with Search Hidden 'False' returned 105 results, showing page 9 of 11.
Result 81 of 105

Test T0200 at 2025-09-30

{'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']}

Configuration
Providergenai
Modelgemini-2.5-flash
  
Temperature0.0
DataclassDocument
  
Normalized Score84.98 %
Test timeunknown seconds
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:

```json
{
  "type": {
    "type": "Dissertation or thesis" OR "Reference"
  },
  "author": {
    "last_name": "string",
    "first_name": "string"
  },
  "publication": {
    "title": "string",
    "year": integer,
    "place": "string or empty string",
    "pages": "string or empty string",
    "publisher": "string or empty string",
    "format": "string or empty string"
  },
  "library_reference": {
    "shelfmark": "string or empty string",
    "subjects": "string or empty string"
  }
}
```

EXTRACTION RULES:
1. **Card Type**: If a card contains the note "s." on a separate line, it is a "Reference". Otherwise, it is a "Dissertation or thesis".

2. **Author**: Extract last_name and first_name. If only one name is given, put it in last_name and leave first_name empty.

3. **Publication**:
   - title: The main title of the work
   - year: Publication year as integer
   - place: Publication place
   - pages: Page count (remove " S." suffix if present)
   - publisher: Publishing house/institution
   - format: Usually "8°", "8'", or "4°" - single value only

4. **Library Reference**:
   - shelfmark: Often begins with "Diss." or "AT", may be marked with "Standort:"
   - subjects: Subject classifications or keywords

5. **Missing Information**: Use empty string "" for missing text fields, omit year fields entirely if not present.

6. **Ignore**: Disregard any information that doesn't fit into these categories.

Return ONLY the JSON object, no additional text or explanation.

Results 

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
n/a 0.86 0.85 0.83 0.88 263 2128 422 287
      Micro Precision Micro Recall Instances TP FP FN
Costs / Pricing
Pricing Date: 6 months ago, 2025-09-30. Tokens: 185.4K IT + 45.1K OT = 230.5K TTCost: 0.056$ + 0.113$ = 0.168$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 82 of 105

Test T0160 at 2025-09-30

{'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']}

Configuration
Provideropenai
Modelgpt-4.1
  
Temperature0.0
DataclassDocument
  
Normalized Score85.38 %
Test timeunknown seconds
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:

```json
{
  "type": {
    "type": "Dissertation or thesis" OR "Reference"
  },
  "author": {
    "last_name": "string",
    "first_name": "string"
  },
  "publication": {
    "title": "string",
    "year": integer,
    "place": "string or empty string",
    "pages": "string or empty string",
    "publisher": "string or empty string",
    "format": "string or empty string"
  },
  "library_reference": {
    "shelfmark": "string or empty string",
    "subjects": "string or empty string"
  }
}
```

EXTRACTION RULES:
1. **Card Type**: If a card contains the note "s." on a separate line, it is a "Reference". Otherwise, it is a "Dissertation or thesis".

2. **Author**: Extract last_name and first_name. If only one name is given, put it in last_name and leave first_name empty.

3. **Publication**:
   - title: The main title of the work
   - year: Publication year as integer
   - place: Publication place
   - pages: Page count (remove " S." suffix if present)
   - publisher: Publishing house/institution
   - format: Usually "8°", "8'", or "4°" - single value only

4. **Library Reference**:
   - shelfmark: Often begins with "Diss." or "AT", may be marked with "Standort:"
   - subjects: Subject classifications or keywords

5. **Missing Information**: Use empty string "" for missing text fields, omit year fields entirely if not present.

6. **Ignore**: Disregard any information that doesn't fit into these categories.

Return ONLY the JSON object, no additional text or explanation.

Results 

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
n/a 0.86 0.85 0.87 0.85 263 2057 316 358
      Micro Precision Micro Recall Instances TP FP FN
Costs / Pricing
Pricing Date: 6 months ago, 2025-09-30. Tokens: 401.3K IT + 245.2K OT = 646.5K TTCost: 0.803$ + 1.962$ = 2.764$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 83 of 105

Test T0066 at 2025-09-30

{'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']}

Configuration
Provideropenai
Modelgpt-4o
  
Temperature0.0
DataclassDocument
  
Normalized Score82.12 %
Test timeunknown seconds
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:

```json
{
  "type": {
    "type": "Dissertation or thesis" OR "Reference"
  },
  "author": {
    "last_name": "string",
    "first_name": "string"
  },
  "publication": {
    "title": "string",
    "year": integer,
    "place": "string or empty string",
    "pages": "string or empty string",
    "publisher": "string or empty string",
    "format": "string or empty string"
  },
  "library_reference": {
    "shelfmark": "string or empty string",
    "subjects": "string or empty string"
  }
}
```

EXTRACTION RULES:
1. **Card Type**: If a card contains the note "s." on a separate line, it is a "Reference". Otherwise, it is a "Dissertation or thesis".

2. **Author**: Extract last_name and first_name. If only one name is given, put it in last_name and leave first_name empty.

3. **Publication**:
   - title: The main title of the work
   - year: Publication year as integer
   - place: Publication place
   - pages: Page count (remove " S." suffix if present)
   - publisher: Publishing house/institution
   - format: Usually "8°", "8'", or "4°" - single value only

4. **Library Reference**:
   - shelfmark: Often begins with "Diss." or "AT", may be marked with "Standort:"
   - subjects: Subject classifications or keywords

5. **Missing Information**: Use empty string "" for missing text fields, omit year fields entirely if not present.

6. **Ignore**: Disregard any information that doesn't fit into these categories.

Return ONLY the JSON object, no additional text or explanation.

Results 

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
n/a 0.82 0.82 0.82 0.82 263 1992 423 423
      Micro Precision Micro Recall Instances TP FP FN
Costs / Pricing
Pricing Date: 6 months ago, 2025-09-30. Tokens: 404.8K IT + 29.1K OT = 433.9K TTCost: 1.012$ + 0.291$ = 1.303$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 84 of 105

Test T0230 at 2025-09-30

{'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']}

Configuration
Provideranthropic
Modelclaude-sonnet-4-5-20250929
  
Temperature0.0
DataclassDocument
  
Normalized Score79.29 %
Test timeunknown seconds
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:

```json
{
  "type": {
    "type": "Dissertation or thesis" OR "Reference"
  },
  "author": {
    "last_name": "string",
    "first_name": "string"
  },
  "publication": {
    "title": "string",
    "year": integer,
    "place": "string or empty string",
    "pages": "string or empty string",
    "publisher": "string or empty string",
    "format": "string or empty string"
  },
  "library_reference": {
    "shelfmark": "string or empty string",
    "subjects": "string or empty string"
  }
}
```

EXTRACTION RULES:
1. **Card Type**: If a card contains the note "s." on a separate line, it is a "Reference". Otherwise, it is a "Dissertation or thesis".

2. **Author**: Extract last_name and first_name. If only one name is given, put it in last_name and leave first_name empty.

3. **Publication**:
   - title: The main title of the work
   - year: Publication year as integer
   - place: Publication place
   - pages: Page count (remove " S." suffix if present)
   - publisher: Publishing house/institution
   - format: Usually "8°", "8'", or "4°" - single value only

4. **Library Reference**:
   - shelfmark: Often begins with "Diss." or "AT", may be marked with "Standort:"
   - subjects: Subject classifications or keywords

5. **Missing Information**: Use empty string "" for missing text fields, omit year fields entirely if not present.

6. **Ignore**: Disregard any information that doesn't fit into these categories.

Return ONLY the JSON object, no additional text or explanation.

Results 

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
n/a 0.81 0.79 0.80 0.81 263 1968 499 447
      Micro Precision Micro Recall Instances TP FP FN
Costs / Pricing
Pricing Date: 6 months ago, 2025-09-30. Tokens: 638.4K IT + 57.2K OT = 695.6K TTCost: 1.915$ + 0.858$ = 2.773$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 85 of 105

Test T0179 at 2025-09-26

{'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']}

Configuration
Providermistral
Modelmistral-medium-2508
  
Temperature0.0
DataclassDocument
  
Normalized Score77.78 %
Test timeunknown seconds
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:

```json
{
  "type": {
    "type": "Dissertation or thesis" OR "Reference"
  },
  "author": {
    "last_name": "string",
    "first_name": "string"
  },
  "publication": {
    "title": "string",
    "year": integer,
    "place": "string or empty string",
    "pages": "string or empty string",
    "publisher": "string or empty string",
    "format": "string or empty string"
  },
  "library_reference": {
    "shelfmark": "string or empty string",
    "subjects": "string or empty string"
  }
}
```

EXTRACTION RULES:
1. **Card Type**: If a card contains the note "s." on a separate line, it is a "Reference". Otherwise, it is a "Dissertation or thesis".

2. **Author**: Extract last_name and first_name. If only one name is given, put it in last_name and leave first_name empty.

3. **Publication**:
   - title: The main title of the work
   - year: Publication year as integer
   - place: Publication place
   - pages: Page count (remove " S." suffix if present)
   - publisher: Publishing house/institution
   - format: Usually "8°", "8'", or "4°" - single value only

4. **Library Reference**:
   - shelfmark: Often begins with "Diss." or "AT", may be marked with "Standort:"
   - subjects: Subject classifications or keywords

5. **Missing Information**: Use empty string "" for missing text fields, omit year fields entirely if not present.

6. **Ignore**: Disregard any information that doesn't fit into these categories.

Return ONLY the JSON object, no additional text or explanation.

Results 

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
n/a 0.78 0.78 0.79 0.77 263 1859 490 556
      Micro Precision Micro Recall Instances TP FP FN
Costs / Pricing
Pricing Date: n/a, n/a. Tokens: n/a IT + n/a OT = n/a TTCost: n/a$ + n/a$ = n/a$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 86 of 105

Test T0180 at 2025-09-26

{'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']}

Configuration
Providermistral
Modelmistral-medium-2505
  
Temperature0.0
DataclassDocument
  
Normalized Score77.55 %
Test timeunknown seconds
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:

```json
{
  "type": {
    "type": "Dissertation or thesis" OR "Reference"
  },
  "author": {
    "last_name": "string",
    "first_name": "string"
  },
  "publication": {
    "title": "string",
    "year": integer,
    "place": "string or empty string",
    "pages": "string or empty string",
    "publisher": "string or empty string",
    "format": "string or empty string"
  },
  "library_reference": {
    "shelfmark": "string or empty string",
    "subjects": "string or empty string"
  }
}
```

EXTRACTION RULES:
1. **Card Type**: If a card contains the note "s." on a separate line, it is a "Reference". Otherwise, it is a "Dissertation or thesis".

2. **Author**: Extract last_name and first_name. If only one name is given, put it in last_name and leave first_name empty.

3. **Publication**:
   - title: The main title of the work
   - year: Publication year as integer
   - place: Publication place
   - pages: Page count (remove " S." suffix if present)
   - publisher: Publishing house/institution
   - format: Usually "8°", "8'", or "4°" - single value only

4. **Library Reference**:
   - shelfmark: Often begins with "Diss." or "AT", may be marked with "Standort:"
   - subjects: Subject classifications or keywords

5. **Missing Information**: Use empty string "" for missing text fields, omit year fields entirely if not present.

6. **Ignore**: Disregard any information that doesn't fit into these categories.

Return ONLY the JSON object, no additional text or explanation.

Results 

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
n/a 0.78 0.78 0.79 0.77 263 1855 497 560
      Micro Precision Micro Recall Instances TP FP FN
Costs / Pricing
Pricing Date: n/a, n/a. Tokens: n/a IT + n/a OT = n/a TTCost: n/a$ + n/a$ = n/a$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 87 of 105

Test T0159 at 2025-09-25

{'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']}

Configuration
Providermistral
Modelpixtral-large-latest
  
Temperature0.0
DataclassDocument
  
Normalized Score77.60 %
Test timeunknown seconds
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:

```json
{
  "type": {
    "type": "Dissertation or thesis" OR "Reference"
  },
  "author": {
    "last_name": "string",
    "first_name": "string"
  },
  "publication": {
    "title": "string",
    "year": integer,
    "place": "string or empty string",
    "pages": "string or empty string",
    "publisher": "string or empty string",
    "format": "string or empty string"
  },
  "library_reference": {
    "shelfmark": "string or empty string",
    "subjects": "string or empty string"
  }
}
```

EXTRACTION RULES:
1. **Card Type**: If a card contains the note "s." on a separate line, it is a "Reference". Otherwise, it is a "Dissertation or thesis".

2. **Author**: Extract last_name and first_name. If only one name is given, put it in last_name and leave first_name empty.

3. **Publication**:
   - title: The main title of the work
   - year: Publication year as integer
   - place: Publication place
   - pages: Page count (remove " S." suffix if present)
   - publisher: Publishing house/institution
   - format: Usually "8°", "8'", or "4°" - single value only

4. **Library Reference**:
   - shelfmark: Often begins with "Diss." or "AT", may be marked with "Standort:"
   - subjects: Subject classifications or keywords

5. **Missing Information**: Use empty string "" for missing text fields, omit year fields entirely if not present.

6. **Ignore**: Disregard any information that doesn't fit into these categories.

Return ONLY the JSON object, no additional text or explanation.

Results 

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
n/a 0.78 0.78 0.77 0.79 263 1900 572 515
      Micro Precision Micro Recall Instances TP FP FN
Costs / Pricing
Pricing Date: n/a, n/a. Tokens: n/a IT + n/a OT = n/a TTCost: n/a$ + n/a$ = n/a$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 88 of 105

Test T0151 at 2025-09-24

{'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']}

Configuration
Providergenai
Modelgemini-2.0-flash
  
Temperature0.0
DataclassDocument
  
Normalized Score84.93 %
Test timeunknown seconds
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:

```json
{
  "type": {
    "type": "Dissertation or thesis" OR "Reference"
  },
  "author": {
    "last_name": "string",
    "first_name": "string"
  },
  "publication": {
    "title": "string",
    "year": integer,
    "place": "string or empty string",
    "pages": "string or empty string",
    "publisher": "string or empty string",
    "format": "string or empty string"
  },
  "library_reference": {
    "shelfmark": "string or empty string",
    "subjects": "string or empty string"
  }
}
```

EXTRACTION RULES:
1. **Card Type**: If a card contains the note "s." on a separate line, it is a "Reference". Otherwise, it is a "Dissertation or thesis".

2. **Author**: Extract last_name and first_name. If only one name is given, put it in last_name and leave first_name empty.

3. **Publication**:
   - title: The main title of the work
   - year: Publication year as integer
   - place: Publication place
   - pages: Page count (remove " S." suffix if present)
   - publisher: Publishing house/institution
   - format: Usually "8°", "8'", or "4°" - single value only

4. **Library Reference**:
   - shelfmark: Often begins with "Diss." or "AT", may be marked with "Standort:"
   - subjects: Subject classifications or keywords

5. **Missing Information**: Use empty string "" for missing text fields, omit year fields entirely if not present.

6. **Ignore**: Disregard any information that doesn't fit into these categories.

Return ONLY the JSON object, no additional text or explanation.

Results 

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
n/a 0.86 0.85 0.85 0.87 263 2089 366 326
      Micro Precision Micro Recall Instances TP FP FN
Costs / Pricing
Pricing Date: n/a, n/a. Tokens: n/a IT + n/a OT = n/a TTCost: n/a$ + n/a$ = n/a$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 89 of 105

Test T0162 at 2025-09-24

{'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']}

Configuration
Provideropenai
Modelgpt-4.1-nano
  
Temperature0.0
DataclassDocument
  
Normalized Score60.41 %
Test timeunknown seconds
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:

```json
{
  "type": {
    "type": "Dissertation or thesis" OR "Reference"
  },
  "author": {
    "last_name": "string",
    "first_name": "string"
  },
  "publication": {
    "title": "string",
    "year": integer,
    "place": "string or empty string",
    "pages": "string or empty string",
    "publisher": "string or empty string",
    "format": "string or empty string"
  },
  "library_reference": {
    "shelfmark": "string or empty string",
    "subjects": "string or empty string"
  }
}
```

EXTRACTION RULES:
1. **Card Type**: If a card contains the note "s." on a separate line, it is a "Reference". Otherwise, it is a "Dissertation or thesis".

2. **Author**: Extract last_name and first_name. If only one name is given, put it in last_name and leave first_name empty.

3. **Publication**:
   - title: The main title of the work
   - year: Publication year as integer
   - place: Publication place
   - pages: Page count (remove " S." suffix if present)
   - publisher: Publishing house/institution
   - format: Usually "8°", "8'", or "4°" - single value only

4. **Library Reference**:
   - shelfmark: Often begins with "Diss." or "AT", may be marked with "Standort:"
   - subjects: Subject classifications or keywords

5. **Missing Information**: Use empty string "" for missing text fields, omit year fields entirely if not present.

6. **Ignore**: Disregard any information that doesn't fit into these categories.

Return ONLY the JSON object, no additional text or explanation.

Results 

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
n/a 0.61 0.60 0.65 0.58 263 1390 738 1025
      Micro Precision Micro Recall Instances TP FP FN
Costs / Pricing
Pricing Date: n/a, n/a. Tokens: n/a IT + n/a OT = n/a TTCost: n/a$ + n/a$ = n/a$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 90 of 105

Test T0164 at 2025-09-02

{'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']}

Configuration
Provideropenai
Modelgpt-4o-mini
  
Temperature0.0
DataclassDocument
  
Normalized Score80.32 %
Test timeunknown seconds
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:

```json
{
  "type": {
    "type": "Dissertation or thesis" OR "Reference"
  },
  "author": {
    "last_name": "string",
    "first_name": "string"
  },
  "publication": {
    "title": "string",
    "year": integer,
    "place": "string or empty string",
    "pages": "string or empty string",
    "publisher": "string or empty string",
    "format": "string or empty string"
  },
  "library_reference": {
    "shelfmark": "string or empty string",
    "subjects": "string or empty string"
  }
}
```

EXTRACTION RULES:
1. **Card Type**: If a card contains the note "s." on a separate line, it is a "Reference". Otherwise, it is a "Dissertation or thesis".

2. **Author**: Extract last_name and first_name. If only one name is given, put it in last_name and leave first_name empty.

3. **Publication**:
   - title: The main title of the work
   - year: Publication year as integer
   - place: Publication place
   - pages: Page count (remove " S." suffix if present)
   - publisher: Publishing house/institution
   - format: Usually "8°", "8'", or "4°" - single value only

4. **Library Reference**:
   - shelfmark: Often begins with "Diss." or "AT", may be marked with "Standort:"
   - subjects: Subject classifications or keywords

5. **Missing Information**: Use empty string "" for missing text fields, omit year fields entirely if not present.

6. **Ignore**: Disregard any information that doesn't fit into these categories.

Return ONLY the JSON object, no additional text or explanation.

Results 

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
n/a 0.81 0.80 0.79 0.83 263 2002 543 413
      Micro Precision Micro Recall Instances TP FP FN
Costs / Pricing
Pricing Date: n/a, n/a. Tokens: n/a IT + n/a OT = n/a TTCost: n/a$ + n/a$ = n/a$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752