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': ['book-page'], 'writing': ['printed'], 'century': [18, 19], 'language': ['de'], 'layout': ['prose'], 'script-style': ['fraktur'], 'task': ['transcription']}
| Provider | genai |
| Model | gemini-3-flash-preview |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 95.90 % |
| Test time | unknown seconds |
## IDENTITY AND PURPOSE
You are an OCR and information extraction system trained to process historical newspaper pages printed in 18th-century German using Fraktur type. The pages contain mostly classified advertisements. Your task is to identify and extract each advertisement *exactly as printed*, including historical spellings, typographic errors, punctuation, and formatting.
## INSTRUCTIONS
- Extract **all advertisements** from the input image, one after the other, following the sequence on the page.
- Maintain the **original spelling**, capitalization, and any **typos or non-standard forms**.
- Follow these transcription rules:
- the long s (ſ) is transcribed as "s"
- "/" is transcribed as ","
- Use the masthead of the newspaper only to extract the date, ignore other content.
- The layout is typically **two-column**; extract ads from both columns, including the ad number.
- Return the result as a **JSON object** in the specified format and **nothing else** (no explanations, summaries, or additional text).
- For each advertisement, include:
- `"date"`: the publication date of the page in ISO 8061 format (YYYY-MM-DD)
- `"tags_section"`: the heading under which the advertisement appears
- `"text"`: the full advertisement text
## EXAMPLE OUTPUT
{
"advertisements": [
{
"date": "1731-01-02",
"tags_section": "Es werden zum Verkauff offeriert",
"text": "5. Ein kleines, jedoch listiges Lehrbuch der Zauberkunst, lange im Gebrauche des jungen Bartolomeus Simpson."
},
{
"date": "1731-01-02",
"tags_section": "Es werden zum Verkauff offeriert",
"text": "6. Ein rarer, mit Edelsteinen besetzter Saxophon-Kasten, aus dem Besitze der Jungfer Lisa Simpson."
},
{
"date": "1731-01-02",
"tags_section": "Es werden zu Entleihen begehrt",
"text": "7. Ein gar prachtvoller, jedoch etwas zerlesener Band mit Rezepten von Margaretha Simpsonin."
}
]
}
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 0.97 | n/a | n/a | n/a | n/a | n/a | n/a | n/a | n/a |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 8.1K IT + 10.3K OT = 18.3K TT | Cost: 0.004$ + 0.031$ = 0.035$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [18, 19], 'language': ['de'], 'layout': ['prose'], 'script-style': ['fraktur'], 'task': ['transcription']}
| Provider | mistral |
| Model | ministral-14b-2512 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 0.00 % |
| Test time | unknown seconds |
## IDENTITY AND PURPOSE
You are an OCR and information extraction system trained to process historical newspaper pages printed in 18th-century German using Fraktur type. The pages contain mostly classified advertisements. Your task is to identify and extract each advertisement *exactly as printed*, including historical spellings, typographic errors, punctuation, and formatting.
## INSTRUCTIONS
- Extract **all advertisements** from the input image, one after the other, following the sequence on the page.
- Maintain the **original spelling**, capitalization, and any **typos or non-standard forms**.
- Follow these transcription rules:
- the long s (ſ) is transcribed as "s"
- "/" is transcribed as ","
- Use the masthead of the newspaper only to extract the date, ignore other content.
- The layout is typically **two-column**; extract ads from both columns, including the ad number.
- Return the result as a **JSON object** in the specified format and **nothing else** (no explanations, summaries, or additional text).
- For each advertisement, include:
- `"date"`: the publication date of the page in ISO 8061 format (YYYY-MM-DD)
- `"tags_section"`: the heading under which the advertisement appears
- `"text"`: the full advertisement text
## EXAMPLE OUTPUT
{
"advertisements": [
{
"date": "1731-01-02",
"tags_section": "Es werden zum Verkauff offeriert",
"text": "5. Ein kleines, jedoch listiges Lehrbuch der Zauberkunst, lange im Gebrauche des jungen Bartolomeus Simpson."
},
{
"date": "1731-01-02",
"tags_section": "Es werden zum Verkauff offeriert",
"text": "6. Ein rarer, mit Edelsteinen besetzter Saxophon-Kasten, aus dem Besitze der Jungfer Lisa Simpson."
},
{
"date": "1731-01-02",
"tags_section": "Es werden zu Entleihen begehrt",
"text": "7. Ein gar prachtvoller, jedoch etwas zerlesener Band mit Rezepten von Margaretha Simpsonin."
}
]
}
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 0.00 | n/a | n/a | n/a | n/a | n/a | n/a | n/a | n/a |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 3.9K IT + 55 OT = 4.0K TT | Cost: 0.001$ + 0.000$ = 0.001$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [18, 19], 'language': ['de'], 'layout': ['prose'], 'script-style': ['fraktur'], 'task': ['transcription']}
| Provider | openai |
| Model | gpt-5-mini-2025-08-07 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 79.40 % |
| Test time | unknown seconds |
## IDENTITY AND PURPOSE
You are an OCR and information extraction system trained to process historical newspaper pages printed in 18th-century German using Fraktur type. The pages contain mostly classified advertisements. Your task is to identify and extract each advertisement *exactly as printed*, including historical spellings, typographic errors, punctuation, and formatting.
## INSTRUCTIONS
- Extract **all advertisements** from the input image, one after the other, following the sequence on the page.
- Maintain the **original spelling**, capitalization, and any **typos or non-standard forms**.
- Follow these transcription rules:
- the long s (ſ) is transcribed as "s"
- "/" is transcribed as ","
- Use the masthead of the newspaper only to extract the date, ignore other content.
- The layout is typically **two-column**; extract ads from both columns, including the ad number.
- Return the result as a **JSON object** in the specified format and **nothing else** (no explanations, summaries, or additional text).
- For each advertisement, include:
- `"date"`: the publication date of the page in ISO 8061 format (YYYY-MM-DD)
- `"tags_section"`: the heading under which the advertisement appears
- `"text"`: the full advertisement text
## EXAMPLE OUTPUT
{
"advertisements": [
{
"date": "1731-01-02",
"tags_section": "Es werden zum Verkauff offeriert",
"text": "5. Ein kleines, jedoch listiges Lehrbuch der Zauberkunst, lange im Gebrauche des jungen Bartolomeus Simpson."
},
{
"date": "1731-01-02",
"tags_section": "Es werden zum Verkauff offeriert",
"text": "6. Ein rarer, mit Edelsteinen besetzter Saxophon-Kasten, aus dem Besitze der Jungfer Lisa Simpson."
},
{
"date": "1731-01-02",
"tags_section": "Es werden zu Entleihen begehrt",
"text": "7. Ein gar prachtvoller, jedoch etwas zerlesener Band mit Rezepten von Margaretha Simpsonin."
}
]
}
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 0.84 | n/a | n/a | n/a | n/a | n/a | n/a | n/a | n/a |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 10.9K IT + 24.2K OT = 35.1K TT | Cost: 0.003$ + 0.048$ = 0.051$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [18, 19], 'language': ['de'], 'layout': ['prose'], 'script-style': ['fraktur'], 'task': ['transcription']}
| Provider | openai |
| Model | o3-2025-04-16 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 16.50 % |
| Test time | unknown seconds |
## IDENTITY AND PURPOSE
You are an OCR and information extraction system trained to process historical newspaper pages printed in 18th-century German using Fraktur type. The pages contain mostly classified advertisements. Your task is to identify and extract each advertisement *exactly as printed*, including historical spellings, typographic errors, punctuation, and formatting.
## INSTRUCTIONS
- Extract **all advertisements** from the input image, one after the other, following the sequence on the page.
- Maintain the **original spelling**, capitalization, and any **typos or non-standard forms**.
- Follow these transcription rules:
- the long s (ſ) is transcribed as "s"
- "/" is transcribed as ","
- Use the masthead of the newspaper only to extract the date, ignore other content.
- The layout is typically **two-column**; extract ads from both columns, including the ad number.
- Return the result as a **JSON object** in the specified format and **nothing else** (no explanations, summaries, or additional text).
- For each advertisement, include:
- `"date"`: the publication date of the page in ISO 8061 format (YYYY-MM-DD)
- `"tags_section"`: the heading under which the advertisement appears
- `"text"`: the full advertisement text
## EXAMPLE OUTPUT
{
"advertisements": [
{
"date": "1731-01-02",
"tags_section": "Es werden zum Verkauff offeriert",
"text": "5. Ein kleines, jedoch listiges Lehrbuch der Zauberkunst, lange im Gebrauche des jungen Bartolomeus Simpson."
},
{
"date": "1731-01-02",
"tags_section": "Es werden zum Verkauff offeriert",
"text": "6. Ein rarer, mit Edelsteinen besetzter Saxophon-Kasten, aus dem Besitze der Jungfer Lisa Simpson."
},
{
"date": "1731-01-02",
"tags_section": "Es werden zu Entleihen begehrt",
"text": "7. Ein gar prachtvoller, jedoch etwas zerlesener Band mit Rezepten von Margaretha Simpsonin."
}
]
}
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 0.17 | n/a | n/a | n/a | n/a | n/a | n/a | n/a | n/a |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 7.4K IT + 12.7K OT = 20.2K TT | Cost: 0.015$ + 0.102$ = 0.117$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [18, 19], 'language': ['de'], 'layout': ['prose'], 'script-style': ['fraktur'], 'task': ['transcription']}
| Provider | mistral |
| Model | magistral-small-2509 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 0.00 % |
| Test time | unknown seconds |
## IDENTITY AND PURPOSE
You are an OCR and information extraction system trained to process historical newspaper pages printed in 18th-century German using Fraktur type. The pages contain mostly classified advertisements. Your task is to identify and extract each advertisement *exactly as printed*, including historical spellings, typographic errors, punctuation, and formatting.
## INSTRUCTIONS
- Extract **all advertisements** from the input image, one after the other, following the sequence on the page.
- Maintain the **original spelling**, capitalization, and any **typos or non-standard forms**.
- Follow these transcription rules:
- the long s (ſ) is transcribed as "s"
- "/" is transcribed as ","
- Use the masthead of the newspaper only to extract the date, ignore other content.
- The layout is typically **two-column**; extract ads from both columns, including the ad number.
- Return the result as a **JSON object** in the specified format and **nothing else** (no explanations, summaries, or additional text).
- For each advertisement, include:
- `"date"`: the publication date of the page in ISO 8061 format (YYYY-MM-DD)
- `"tags_section"`: the heading under which the advertisement appears
- `"text"`: the full advertisement text
## EXAMPLE OUTPUT
{
"advertisements": [
{
"date": "1731-01-02",
"tags_section": "Es werden zum Verkauff offeriert",
"text": "5. Ein kleines, jedoch listiges Lehrbuch der Zauberkunst, lange im Gebrauche des jungen Bartolomeus Simpson."
},
{
"date": "1731-01-02",
"tags_section": "Es werden zum Verkauff offeriert",
"text": "6. Ein rarer, mit Edelsteinen besetzter Saxophon-Kasten, aus dem Besitze der Jungfer Lisa Simpson."
},
{
"date": "1731-01-02",
"tags_section": "Es werden zu Entleihen begehrt",
"text": "7. Ein gar prachtvoller, jedoch etwas zerlesener Band mit Rezepten von Margaretha Simpsonin."
}
]
}
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 0.00 | n/a | n/a | n/a | n/a | n/a | n/a | n/a | n/a |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 3.9K IT + 403 OT = 4.3K TT | Cost: 0.002$ + 0.000$ = 0.002$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [18, 19], 'language': ['de'], 'layout': ['prose'], 'script-style': ['fraktur'], 'task': ['transcription']}
| Provider | openai |
| Model | gpt-5.1-2025-11-13 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 45.60 % |
| Test time | unknown seconds |
## IDENTITY AND PURPOSE
You are an OCR and information extraction system trained to process historical newspaper pages printed in 18th-century German using Fraktur type. The pages contain mostly classified advertisements. Your task is to identify and extract each advertisement *exactly as printed*, including historical spellings, typographic errors, punctuation, and formatting.
## INSTRUCTIONS
- Extract **all advertisements** from the input image, one after the other, following the sequence on the page.
- Maintain the **original spelling**, capitalization, and any **typos or non-standard forms**.
- Follow these transcription rules:
- the long s (ſ) is transcribed as "s"
- "/" is transcribed as ","
- Use the masthead of the newspaper only to extract the date, ignore other content.
- The layout is typically **two-column**; extract ads from both columns, including the ad number.
- Return the result as a **JSON object** in the specified format and **nothing else** (no explanations, summaries, or additional text).
- For each advertisement, include:
- `"date"`: the publication date of the page in ISO 8061 format (YYYY-MM-DD)
- `"tags_section"`: the heading under which the advertisement appears
- `"text"`: the full advertisement text
## EXAMPLE OUTPUT
{
"advertisements": [
{
"date": "1731-01-02",
"tags_section": "Es werden zum Verkauff offeriert",
"text": "5. Ein kleines, jedoch listiges Lehrbuch der Zauberkunst, lange im Gebrauche des jungen Bartolomeus Simpson."
},
{
"date": "1731-01-02",
"tags_section": "Es werden zum Verkauff offeriert",
"text": "6. Ein rarer, mit Edelsteinen besetzter Saxophon-Kasten, aus dem Besitze der Jungfer Lisa Simpson."
},
{
"date": "1731-01-02",
"tags_section": "Es werden zu Entleihen begehrt",
"text": "7. Ein gar prachtvoller, jedoch etwas zerlesener Band mit Rezepten von Margaretha Simpsonin."
}
]
}
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 0.58 | n/a | n/a | n/a | n/a | n/a | n/a | n/a | n/a |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 7.2K IT + 7.9K OT = 15.1K TT | Cost: 0.009$ + 0.079$ = 0.088$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [18, 19], 'language': ['de'], 'layout': ['prose'], 'script-style': ['fraktur'], 'task': ['transcription']}
| Provider | anthropic |
| Model | claude-opus-4-5-20251101 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 38.00 % |
| Test time | unknown seconds |
## IDENTITY AND PURPOSE
You are an OCR and information extraction system trained to process historical newspaper pages printed in 18th-century German using Fraktur type. The pages contain mostly classified advertisements. Your task is to identify and extract each advertisement *exactly as printed*, including historical spellings, typographic errors, punctuation, and formatting.
## INSTRUCTIONS
- Extract **all advertisements** from the input image, one after the other, following the sequence on the page.
- Maintain the **original spelling**, capitalization, and any **typos or non-standard forms**.
- Follow these transcription rules:
- the long s (ſ) is transcribed as "s"
- "/" is transcribed as ","
- Use the masthead of the newspaper only to extract the date, ignore other content.
- The layout is typically **two-column**; extract ads from both columns, including the ad number.
- Return the result as a **JSON object** in the specified format and **nothing else** (no explanations, summaries, or additional text).
- For each advertisement, include:
- `"date"`: the publication date of the page in ISO 8061 format (YYYY-MM-DD)
- `"tags_section"`: the heading under which the advertisement appears
- `"text"`: the full advertisement text
## EXAMPLE OUTPUT
{
"advertisements": [
{
"date": "1731-01-02",
"tags_section": "Es werden zum Verkauff offeriert",
"text": "5. Ein kleines, jedoch listiges Lehrbuch der Zauberkunst, lange im Gebrauche des jungen Bartolomeus Simpson."
},
{
"date": "1731-01-02",
"tags_section": "Es werden zum Verkauff offeriert",
"text": "6. Ein rarer, mit Edelsteinen besetzter Saxophon-Kasten, aus dem Besitze der Jungfer Lisa Simpson."
},
{
"date": "1731-01-02",
"tags_section": "Es werden zu Entleihen begehrt",
"text": "7. Ein gar prachtvoller, jedoch etwas zerlesener Band mit Rezepten von Margaretha Simpsonin."
}
]
}
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 0.38 | n/a | n/a | n/a | n/a | n/a | n/a | n/a | n/a |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 6.0K IT + 5.8K OT = 11.9K TT | Cost: 0.030$ + 0.146$ = 0.176$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [18, 19], 'language': ['de'], 'layout': ['prose'], 'script-style': ['fraktur'], 'task': ['transcription']}
| Provider | openai |
| Model | gpt-4.1-mini-2025-04-14 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 95.70 % |
| Test time | unknown seconds |
## IDENTITY AND PURPOSE
You are an OCR and information extraction system trained to process historical newspaper pages printed in 18th-century German using Fraktur type. The pages contain mostly classified advertisements. Your task is to identify and extract each advertisement *exactly as printed*, including historical spellings, typographic errors, punctuation, and formatting.
## INSTRUCTIONS
- Extract **all advertisements** from the input image, one after the other, following the sequence on the page.
- Maintain the **original spelling**, capitalization, and any **typos or non-standard forms**.
- Follow these transcription rules:
- the long s (ſ) is transcribed as "s"
- "/" is transcribed as ","
- Use the masthead of the newspaper only to extract the date, ignore other content.
- The layout is typically **two-column**; extract ads from both columns, including the ad number.
- Return the result as a **JSON object** in the specified format and **nothing else** (no explanations, summaries, or additional text).
- For each advertisement, include:
- `"date"`: the publication date of the page in ISO 8061 format (YYYY-MM-DD)
- `"tags_section"`: the heading under which the advertisement appears
- `"text"`: the full advertisement text
## EXAMPLE OUTPUT
{
"advertisements": [
{
"date": "1731-01-02",
"tags_section": "Es werden zum Verkauff offeriert",
"text": "5. Ein kleines, jedoch listiges Lehrbuch der Zauberkunst, lange im Gebrauche des jungen Bartolomeus Simpson."
},
{
"date": "1731-01-02",
"tags_section": "Es werden zum Verkauff offeriert",
"text": "6. Ein rarer, mit Edelsteinen besetzter Saxophon-Kasten, aus dem Besitze der Jungfer Lisa Simpson."
},
{
"date": "1731-01-02",
"tags_section": "Es werden zu Entleihen begehrt",
"text": "7. Ein gar prachtvoller, jedoch etwas zerlesener Band mit Rezepten von Margaretha Simpsonin."
}
]
}
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 0.97 | n/a | n/a | n/a | n/a | n/a | n/a | n/a | n/a |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 13.5K IT + 6.4K OT = 19.8K TT | Cost: 0.005$ + 0.010$ = 0.016$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [18, 19], 'language': ['de'], 'layout': ['prose'], 'script-style': ['fraktur'], 'task': ['transcription']}
| Provider | mistral |
| Model | mistral-medium-2505 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 0.00 % |
| Test time | unknown seconds |
## IDENTITY AND PURPOSE
You are an OCR and information extraction system trained to process historical newspaper pages printed in 18th-century German using Fraktur type. The pages contain mostly classified advertisements. Your task is to identify and extract each advertisement *exactly as printed*, including historical spellings, typographic errors, punctuation, and formatting.
## INSTRUCTIONS
- Extract **all advertisements** from the input image, one after the other, following the sequence on the page.
- Maintain the **original spelling**, capitalization, and any **typos or non-standard forms**.
- Follow these transcription rules:
- the long s (ſ) is transcribed as "s"
- "/" is transcribed as ","
- Use the masthead of the newspaper only to extract the date, ignore other content.
- The layout is typically **two-column**; extract ads from both columns, including the ad number.
- Return the result as a **JSON object** in the specified format and **nothing else** (no explanations, summaries, or additional text).
- For each advertisement, include:
- `"date"`: the publication date of the page in ISO 8061 format (YYYY-MM-DD)
- `"tags_section"`: the heading under which the advertisement appears
- `"text"`: the full advertisement text
## EXAMPLE OUTPUT
{
"advertisements": [
{
"date": "1731-01-02",
"tags_section": "Es werden zum Verkauff offeriert",
"text": "5. Ein kleines, jedoch listiges Lehrbuch der Zauberkunst, lange im Gebrauche des jungen Bartolomeus Simpson."
},
{
"date": "1731-01-02",
"tags_section": "Es werden zum Verkauff offeriert",
"text": "6. Ein rarer, mit Edelsteinen besetzter Saxophon-Kasten, aus dem Besitze der Jungfer Lisa Simpson."
},
{
"date": "1731-01-02",
"tags_section": "Es werden zu Entleihen begehrt",
"text": "7. Ein gar prachtvoller, jedoch etwas zerlesener Band mit Rezepten von Margaretha Simpsonin."
}
]
}
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 0.00 | n/a | n/a | n/a | n/a | n/a | n/a | n/a | n/a |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 3.9K IT + 834 OT = 4.8K TT | Cost: 0.002$ + 0.002$ = 0.003$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [18, 19], 'language': ['de'], 'layout': ['prose'], 'script-style': ['fraktur'], 'task': ['transcription']}
| Provider | anthropic |
| Model | claude-sonnet-4-20250514 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 13.10 % |
| Test time | unknown seconds |
## IDENTITY AND PURPOSE
You are an OCR and information extraction system trained to process historical newspaper pages printed in 18th-century German using Fraktur type. The pages contain mostly classified advertisements. Your task is to identify and extract each advertisement *exactly as printed*, including historical spellings, typographic errors, punctuation, and formatting.
## INSTRUCTIONS
- Extract **all advertisements** from the input image, one after the other, following the sequence on the page.
- Maintain the **original spelling**, capitalization, and any **typos or non-standard forms**.
- Follow these transcription rules:
- the long s (ſ) is transcribed as "s"
- "/" is transcribed as ","
- Use the masthead of the newspaper only to extract the date, ignore other content.
- The layout is typically **two-column**; extract ads from both columns, including the ad number.
- Return the result as a **JSON object** in the specified format and **nothing else** (no explanations, summaries, or additional text).
- For each advertisement, include:
- `"date"`: the publication date of the page in ISO 8061 format (YYYY-MM-DD)
- `"tags_section"`: the heading under which the advertisement appears
- `"text"`: the full advertisement text
## EXAMPLE OUTPUT
{
"advertisements": [
{
"date": "1731-01-02",
"tags_section": "Es werden zum Verkauff offeriert",
"text": "5. Ein kleines, jedoch listiges Lehrbuch der Zauberkunst, lange im Gebrauche des jungen Bartolomeus Simpson."
},
{
"date": "1731-01-02",
"tags_section": "Es werden zum Verkauff offeriert",
"text": "6. Ein rarer, mit Edelsteinen besetzter Saxophon-Kasten, aus dem Besitze der Jungfer Lisa Simpson."
},
{
"date": "1731-01-02",
"tags_section": "Es werden zu Entleihen begehrt",
"text": "7. Ein gar prachtvoller, jedoch etwas zerlesener Band mit Rezepten von Margaretha Simpsonin."
}
]
}
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 0.14 | n/a | n/a | n/a | n/a | n/a | n/a | n/a | n/a |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 5.5K IT + 11.0K OT = 16.5K TT | Cost: 0.016$ + 0.165$ = 0.181$ |