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-2.5-flash-lite-preview-09-2025 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 46.30 % |
| 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 | |||||
| 0.51 | 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: 6 months ago, 2025-10-01. | Tokens: 3.9K IT + 13.5K OT = 17.4K TT | Cost: 0.000$ + 0.005$ = 0.006$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [18, 19], 'language': ['de'], 'layout': ['prose'], 'script-style': ['fraktur'], 'task': ['transcription']}
| Provider | openai |
| Model | o3 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 12.00 % |
| 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 | |||||
| 0.14 | 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: 6 months ago, 2025-10-01. | Tokens: 6.6K IT + 16.9K OT = 23.5K TT | Cost: 0.013$ + 0.135$ = 0.148$ |
{'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 | 37.00 % |
| 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 | |||||
| 0.43 | 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: 6 months ago, 2025-10-01. | Tokens: 8.8K IT + 8.8K OT = 17.6K TT | Cost: 0.004$ + 0.018$ = 0.021$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [18, 19], 'language': ['de'], 'layout': ['prose'], 'script-style': ['fraktur'], 'task': ['transcription']}
| Provider | genai |
| Model | gemini-2.5-flash-lite |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 58.70 % |
| 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 | |||||
| 0.63 | 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: 6 months ago, 2025-10-01. | Tokens: 3.9K IT + 10.3K OT = 14.2K TT | Cost: 0.000$ + 0.004$ = 0.005$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [18, 19], 'language': ['de'], 'layout': ['prose'], 'script-style': ['fraktur'], 'task': ['transcription']}
| Provider | mistral |
| Model | mistral-medium-2508 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 28.60 % |
| 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 | |||||
| 0.33 | 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: 6 months ago, 2025-10-01. | Tokens: 8.8K IT + 8.9K OT = 17.7K TT | Cost: 0.004$ + 0.018$ = 0.021$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [18, 19], 'language': ['de'], 'layout': ['prose'], 'script-style': ['fraktur'], 'task': ['transcription']}
| Provider | genai |
| Model | gemini-2.5-pro |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 95.00 % |
| 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 | |||||
| 0.96 | 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: 6 months ago, 2025-10-01. | Tokens: 3.9K IT + 10.2K OT = 14.1K TT | Cost: 0.005$ + 0.102$ = 0.107$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [18, 19], 'language': ['de'], 'layout': ['prose'], 'script-style': ['fraktur'], 'task': ['transcription']}
| Provider | mistral |
| Model | mistral-large-latest |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 45.30 % |
| 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 | |||||
| 0.51 | 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: 6 months ago, 2025-10-01. | Tokens: 8.8K IT + 8.5K OT = 17.3K TT | Cost: 0.018$ + 0.051$ = 0.068$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [18, 19], 'language': ['de'], 'layout': ['prose'], 'script-style': ['fraktur'], 'task': ['transcription']}
| Provider | openai |
| Model | gpt-4.1 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 50.20 % |
| 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 | |||||
| 0.57 | 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: 6 months ago, 2025-09-30. | Tokens: 7.0K IT + 7.9K OT = 15.0K TT | Cost: 0.014$ + 0.064$ = 0.078$ |
{'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 | 32.30 % |
| 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 | |||||
| 0.36 | 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: 6 months ago, 2025-09-30. | Tokens: 10.7K IT + 11.8K OT = 22.4K TT | Cost: 0.032$ + 0.176$ = 0.208$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [18, 19], 'language': ['de'], 'layout': ['prose'], 'script-style': ['fraktur'], 'task': ['transcription']}
| Provider | openai |
| Model | gpt-4o |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 40.50 % |
| 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 | |||||
| 0.48 | 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: 6 months ago, 2025-09-30. | Tokens: 7.0K IT + 6.1K OT = 13.2K TT | Cost: 0.018$ + 0.061$ = 0.079$ |