form listlengths 11 181 |
|---|
[
{
"box": [
292,
91,
376,
175
],
"text": "R&D",
"label": "other",
"words": [
{
"box": [
292,
91,
376,
175
],
"text": "R&D"
}
],
"linking": [],
"id": 0
},
{
"box": [
219,
... |
[
{
"box": [
76,
129,
118,
139
],
"text": "Brand:",
"label": "question",
"words": [
{
"box": [
76,
129,
118,
139
],
"text": "Brand:"
}
],
"linking": [
[
0,
2
]
... |
[
{
"box": [
61,
207,
97,
221
],
"text": "DATE:",
"label": "question",
"words": [
{
"box": [
61,
207,
97,
221
],
"text": "DATE:"
}
],
"linking": [
[
0,
16
]
]... |
[
{
"box": [
60,
121,
127,
135
],
"text": "SUBJECT:",
"label": "question",
"words": [
{
"box": [
60,
121,
127,
135
],
"text": "SUBJECT:"
}
],
"linking": [
[
0,
146
... |
[
{
"box": [
221,
71,
264,
89
],
"text": "B&W",
"label": "header",
"words": [
{
"box": [
221,
71,
264,
89
],
"text": "B&W"
}
],
"linking": [],
"id": 0
},
{
"box": [
221,
... |
[
{
"box": [
10,
166,
48,
179
],
"text": "DATE:",
"label": "question",
"words": [
{
"box": [
10,
166,
48,
179
],
"text": "DATE:"
}
],
"linking": [
[
0,
13
]
]... |
[
{
"box": [
96,
177,
118,
192
],
"text": "FAX:",
"label": "question",
"words": [
{
"box": [
96,
177,
118,
192
],
"text": "FAX:"
}
],
"linking": [
[
0,
18
]
]... |
[
{
"box": [
41,
127,
84,
144
],
"text": "Brand",
"label": "question",
"words": [
{
"box": [
41,
127,
84,
144
],
"text": "Brand"
}
],
"linking": [
[
0,
46
]
]... |
[
{
"box": [
112,
209,
123,
217
],
"text": "",
"label": "other",
"words": [
{
"box": [
112,
209,
123,
217
],
"text": ""
}
],
"linking": [],
"id": 0
},
{
"box": [
123,
... |
[
{
"box": [
45,
209,
91,
224
],
"text": "Title",
"label": "question",
"words": [
{
"box": [
45,
209,
91,
224
],
"text": "Title"
}
],
"linking": [
[
0,
52
]
]... |
[
{
"box": [
76,
67,
118,
82
],
"text": "SECRET",
"label": "other",
"words": [
{
"box": [
76,
67,
118,
82
],
"text": "SECRET"
}
],
"linking": [],
"id": 0
},
{
"box": [
69,
... |
[
{
"box": [
78,
70,
114,
84
],
"text": "Date:",
"label": "question",
"words": [
{
"box": [
78,
70,
114,
84
],
"text": "Date:"
}
],
"linking": [],
"id": 0
},
{
"box": [
78,... |
[
{
"box": [
96,
282,
104,
295
],
"text": "(",
"label": "other",
"words": [
{
"box": [
96,
282,
104,
295
],
"text": "("
}
],
"linking": [],
"id": 0
},
{
"box": [
130,
... |
[
{
"box": [
505,
427,
575,
439
],
"text": "COMMENTS",
"label": "question",
"words": [
{
"box": [
505,
427,
575,
439
],
"text": "COMMENTS"
}
],
"linking": [
[
0,
47
... |
End of preview. Expand in Data Studio
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
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:
linkingfield 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 |
- Downloads last month
- 19