Datasets:
Update benchmark results (82.2% on 451 samples)
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- predictions/484.html +79 -82
README.md
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@@ -33,7 +33,7 @@ Benchmark results for [DocLD](https://docld.com) table extraction on the
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## Methodology
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- **Dataset**: [FinTabNet_OTSL](https://huggingface.co/datasets/docling-project/FinTabNet_OTSL) — 500 samples from the test split
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- **Extraction**: DocLD
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- **Scoring**: Needleman-Wunsch hierarchical alignment (same as [RD-TableBench](https://github.com/reductoai/rd-tablebench))
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- **Output**: HTML tables with rowspan/colspan for merged cells
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## Methodology
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- **Dataset**: [FinTabNet_OTSL](https://huggingface.co/datasets/docling-project/FinTabNet_OTSL) — 500 samples from the test split
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- **Extraction**: DocLD vision-based table extraction
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- **Scoring**: Needleman-Wunsch hierarchical alignment (same as [RD-TableBench](https://github.com/reductoai/rd-tablebench))
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- **Output**: HTML tables with rowspan/colspan for merged cells
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predictions/484.html
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<table>
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<th></th>
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<th>2018</th>
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<th>2017</th>
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<th></th>
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<th colspan="2">(In millions)</th>
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<td>$ 8,299.3</td>
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</table>
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<table>
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<tr>
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<th></th>
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<th>December 31,</th>
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<th></th>
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<th>2018</th>
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<th>2017</th>
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<th></th>
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<th colspan="2">(In millions)</th>
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<td>Assets:</td>
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<td></td>
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<td></td>
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</tr>
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<td>Cash and cash equivalents</td>
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<td>$ 0.1</td>
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<td>$ 0.1</td>
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<td>Investment in subsidiaries</td>
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<td>8,606.0</td>
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<td>8,203.9</td>
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<td>Other assets</td>
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<td>20.1</td>
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<td>95.3</td>
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</tr>
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<tr>
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<td>Total assets</td>
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<td>$ 8,626.2</td>
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<td>$ 8,299.3</td>
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<td>Liabilities:</td>
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<td></td>
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<td>Current debt</td>
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<td>$ 114.4</td>
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<td>$ 76.2</td>
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<td>Long-term debt</td>
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<td>5,427.7</td>
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<td>5,797.5</td>
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</tr>
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<td>Intercompany liabilities</td>
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<td>395.9</td>
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<td>177.8</td>
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</tr>
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<td>Other liabilities</td>
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<td>356.1</td>
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<td>392.5</td>
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</tr>
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<tr>
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<td>Total liabilities</td>
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<td>6,294.1</td>
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<td>6,444.0</td>
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</tr>
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<td>Stockholders’ equity</td>
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<td>2,332.1</td>
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<td>1,855.3</td>
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</tr>
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<td>Total liabilities and stockholders’ equity</td>
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<td>$ 8,626.2</td>
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<td>$ 8,299.3</td>
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</tr>
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</table>
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