Datasets:

docld
/

fintabnet-bench

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Table Question Answering

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table-extraction

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train · 6 rows

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DocLD FinTabNet Benchmark Results

Benchmark results for DocLD table extraction on the FinTabNet dataset.

Results Summary

Metric	Value
Mean Accuracy	82.1%
Median	83.2%
P25 / P75	73.3% / 97.4%
Min / Max	22.7% / 100.0%
Scored Samples	500
Total Samples	500

Methodology

Dataset: FinTabNet_OTSL — 500 samples from the test split
Extraction: DocLD vision-based table extraction
Scoring: Needleman-Wunsch hierarchical alignment (same as RD-TableBench)
Output: HTML tables with rowspan/colspan for merged cells

Comparison

Provider	FinTabNet Accuracy
DocLD	82.1%
GTE (IBM)	~78%
TATR (Microsoft)	~65%

Files

results.json — Full benchmark results with per-sample scores
predictions/ — HTML predictions for each sample
charts/ — Visualization PNGs

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