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:
Together, test runs make it possible to compare models, providers, and configurations across benchmarks in a transparent and reproducible way.
{'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']}
| Provider | openai |
| Model | gpt-4o-2024-08-06 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 84.97 % |
| Test time | unknown seconds |
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.
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.86 | 0.85 | 0.86 | 0.85 | 263 | 2059 | 332 | 356 |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 462.1K IT + 30.8K OT = 492.8K TT | Cost: 1.155$ + 0.308$ = 1.463$ |
{'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']}
| Provider | anthropic |
| Model | claude-sonnet-4-5-20250929 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 84.70 % |
| Test time | unknown seconds |
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.
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.86 | 0.85 | 0.84 | 0.87 | 263 | 2112 | 395 | 303 |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 706.0K IT + 56.2K OT = 762.1K TT | Cost: 2.118$ + 0.842$ = 2.960$ |
{'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']}
| Provider | anthropic |
| Model | claude-opus-4-1-20250805 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 81.96 % |
| Test time | unknown seconds |
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.
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.83 | 0.82 | 0.81 | 0.84 | 263 | 2033 | 462 | 382 |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 634.2K IT + 54.9K OT = 689.1K TT | Cost: 9.513$ + 4.118$ = 13.631$ |
{'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']}
| Provider | genai |
| Model | gemini-2.5-pro |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 86.39 % |
| Test time | unknown seconds |
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.
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.87 | 0.86 | 0.85 | 0.89 | 263 | 2147 | 385 | 268 |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 187.3K IT + 48.9K OT = 236.2K TT | Cost: 0.234$ + 0.489$ = 0.723$ |
{'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']}
| Provider | openai |
| Model | gpt-5.1-2025-11-13 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 81.82 % |
| Test time | unknown seconds |
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.
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.82 | 0.82 | 0.82 | 0.82 | 263 | 1979 | 422 | 436 |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 365.2K IT + 33.2K OT = 398.4K TT | Cost: 0.456$ + 0.332$ = 0.789$ |
{'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']}
| Provider | genai |
| Model | gemini-2.5-flash |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 86.02 % |
| Test time | unknown seconds |
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.
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.87 | 0.86 | 0.85 | 0.89 | 263 | 2141 | 389 | 274 |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 187.3K IT + 38.2K OT = 225.5K TT | Cost: 0.056$ + 0.096$ = 0.152$ |
{'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']}
| Provider | openrouter |
| Model | meta-llama/llama-4-maverick |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 62.33 % |
| Test time | unknown seconds |
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.
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.67 | 0.62 | 0.78 | 0.59 | 263 | 1433 | 399 | 982 |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: 9 months ago, 2025-10-17. | Tokens: 390.9K IT + 819.9K OT = 1.2M TT | Cost: 0.059$ + 0.492$ = 0.551$ |
{'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']}
| Provider | openrouter |
| Model | qwen/qwen3-vl-8b-thinking |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 5.90 % |
| Test time | unknown seconds |
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.
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.10 | 0.06 | 0.33 | 0.06 | 263 | 148 | 305 | 2267 |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: 9 months ago, 2025-10-17. | Tokens: 495.2K IT + 44.6K OT = 539.8K TT | Cost: 0.089$ + 0.094$ = 0.183$ |
{'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']}
| Provider | openai |
| Model | gpt-4o-mini |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 0.95 % |
| Test time | unknown seconds |
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.
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.01 | 0.01 | 0.07 | 0.01 | 263 | 20 | 275 | 2395 |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: 9 months ago, 2025-10-03. | Tokens: 131.3K IT + 727 OT = 132.0K TT | Cost: 0.020$ + 0.000$ = 0.020$ |
{'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']}
| Provider | openai |
| Model | gpt-4.1-nano |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 66.70 % |
| Test time | unknown seconds |
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.
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.68 | 0.67 | 0.72 | 0.64 | 263 | 1536 | 592 | 879 |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: None, None. | Tokens: None IT + None OT = None TT | Cost: None$ + None$ = None$ |