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 10 of 11.
Result 91 of 105

Test T0066 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
  
Temperature0.0
DataclassDocument
  
Normalized Score89.36 %
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 0.90 0.89 0.91 0.88 263 2125 203 290
      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 92 of 105

Test T0160 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-4.1
  
Temperature0.0
DataclassDocument
  
Normalized Score89.39 %
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 0.90 0.89 0.91 0.88 263 2131 205 284
      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 93 of 105

Test T0162 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-4.1-nano
  
Temperature0.0
DataclassDocument
  
Normalized Score71.79 %
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 0.73 0.72 0.77 0.69 263 1671 494 744
      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 94 of 105

Test T0165 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-5
  
Temperature0.0
DataclassDocument
  
Normalized Score89.51 %
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 0.90 0.90 0.92 0.88 263 2122 193 293
      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 95 of 105

Test T0146 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
Provideranthropic
Modelclaude-opus-4-1-20250805
  
Temperature0.0
DataclassDocument
  
Normalized Score83.33 %
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 0.84 0.83 0.86 0.83 263 1996 315 419
      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 96 of 105

Test T0152 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
Providergenai
Modelgemini-2.0-flash-lite
  
Temperature0.0
DataclassDocument
  
Normalized Score86.52 %
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 0.87 0.87 0.88 0.86 263 2084 288 331
      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 97 of 105

Test T0161 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-4.1-mini
  
Temperature0.0
DataclassDocument
  
Normalized Score86.74 %
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 0.87 0.87 0.89 0.85 263 2061 261 354
      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 98 of 105

Test T0167 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-5-nano
  
Temperature0.0
DataclassDocument
  
Normalized Score79.70 %
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 0.80 0.80 0.79 0.82 263 1969 526 446
      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 99 of 105

Test T0166 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-5-mini
  
Temperature0.0
DataclassDocument
  
Normalized Score84.05 %
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 0.84 0.84 0.90 0.79 263 1916 209 499
      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 100 of 105

Test T0151 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
Providergenai
Modelgemini-2.0-flash
  
Temperature0.0
DataclassDocument
  
Normalized Score82.97 %
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 0.84 0.83 0.85 0.82 263 1988 345 427
      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