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SER & RE Training Data

Datasets for Semantic Entity Recognition (SER) and Relation Extraction (RE) training.

Datasets

1. XFUND (~/data/ser_re/xfund/)

  • Source: https://github.com/doc-analysis/XFUND/releases/tag/v1.0
  • Languages: zh, ja, es, fr, it, de, pt (7 languages)
  • Documents: 149 train + 50 val per language = 1,393 total
  • Images: 1,393 JPG files ({lang}{split}{idx}.jpg)
  • Annotations: {lang}.train.json / {lang}.val.json
  • Format: Word-level bboxes, BIO labels (question/answer/header/other), entity linking (Q->A pairs)
  • Linking pairs: ~80,000 train + ~25,000 val across all languages
  • License: CC BY-NC-SA 4.0
  • Label distribution (train, all languages combined):
    • question: ~21,462
    • answer: ~30,510
    • header: ~1,321
    • other: ~18,706

2. FUNSD (~/data/ser_re/funsd/)

  • Source: https://guillaumejaume.github.io/FUNSD/
  • Language: English
  • Documents: 149 train + 50 test = 199 total
  • Images: 199 PNG files in dataset/{split}_data/images/
  • Annotations: JSON files in dataset/{split}_data/annotations/
  • Format: Entity-level bboxes with word-level sub-boxes, labels (question/answer/header/other), entity linking
  • Linking pairs: 8,472 train + 2,152 test = 10,624 total
  • License: CC BY-NC-SA 4.0 (derived from RVL-CDIP / tobacco litigation docs)
  • Label distribution:
    • Train: 3,266 question, 2,802 answer, 441 header, 902 other
    • Test: 1,077 question, 821 answer, 122 header, 312 other

3. DocILE (~/data/ser_re/docile/) -- NOT YET DOWNLOADED

  • Source: https://docile.rossum.ai/
  • Requires manual registration: Fill form at https://forms.gle/poJqGXrxoftWrUsc8
  • Documents: 6,680 annotated + 100,000 synthetic + ~1M unlabeled
  • Task: Key Information Extraction (KIE) + Line Item Recognition (LIR)
  • Format: PDF documents with field-level annotations (bboxes + field types)
  • License: Research use only (requires legal agreement)
  • Python package: pip3 install docile-benchmark
  • See docile/README.md for download instructions

Annotation Format Summary

All datasets use a similar annotation structure:

  • SER labels: question, answer, header, other (BIO tagging at word or entity level)
  • RE annotations: linking field with pairs of (source_id, target_id) mapping questions to answers
  • Bounding boxes: [x0, y0, x1, y1] pixel coordinates (XFUND uses 0-1000 normalized coords)

Combined Stats (excluding DocILE)

Dataset Language Train Docs Val/Test Docs Total Linking Pairs
XFUND zh 149 50 17,238
XFUND ja 149 50 12,130
XFUND es 149 50 15,268
XFUND fr 149 50 11,275
XFUND it 149 50 13,790
XFUND de 149 50 14,568
XFUND pt 149 50 18,022
FUNSD en 149 50 10,624
Total 1,341 450 112,915