Datasets:
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license: cc-by-sa-4.0
pretty_name: Doc-Split Benchmark (page-stream segmentation)
task_categories: [image-classification, text-classification]
language: [multilingual]
tags: [page-stream-segmentation, document-boundary-detection, document-ai, benchmark]
size_categories: [1K<n<10K]
configs:
- config_name: our200
data_files: [{split: test, path: our200/test-*.parquet}]
---
# Doc-Split Benchmark
The **evaluation slice** for page-stream segmentation — the exact set behind the
[leaderboard](https://huggingface.co/spaces/nutrientdocs/doc-split-leaderboard) and the cloud-VLM
comparison. Self-contained (page images embedded), with a reference scorer so results are reproducible.
This is the *benchmark*, not the training corpus (which stays private).
- 🏆 **Leaderboard:** [doc-split-leaderboard](https://huggingface.co/spaces/nutrientdocs/doc-split-leaderboard)
- 🎯 **Demo:** [doc-split-demo](https://huggingface.co/spaces/nutrientdocs/doc-split-demo)
- 🟢 **Model:** [doc-split-mini-e5](https://huggingface.co/nutrientdocs/doc-split-mini-e5) (open weights)
- 🌍 **OpenPSS cuts:** [openpss-mirror](https://huggingface.co/datasets/nutrientdocs/openpss-mirror) (SHORT/LONG, self-contained)
## Cuts
| Cut | Where | Notes |
|---|---|---|
| **our-200** | this repo (`our200` config) | 200 license-clean synthetic-concat streams, ~78% boundary rate |
| **OpenPSS short / long** | [openpss-mirror](https://huggingface.co/datasets/nutrientdocs/openpss-mirror) | Dutch; sparse- & dense-boundary regimes |
| TABME++ / Tobacco800 | upstream (not redistributed) | reported for reference; licenses/gating prevent re-hosting |
## Load
```python
from datasets import load_dataset
ds = load_dataset("nutrientdocs/doc-split-benchmark", "our200", split="test")
# one row = one page; group by stream_id, order by position.
```
## Schema
| Field | Type | Meaning |
|---|---|---|
| `stream_id` | string | groups pages into one ordered stream |
| `position` | int | page index within the stream (0-based) |
| `boundary` | int | **1 = starts a new document** (position 0 always 1) |
| `page_text` | string | page OCR text (may be empty) |
| `image` | image | page image (512px) |
| `source` | string | provenance |
## How to score
Metric: **boundary page-F1** (internal positions, page 0 forced) + Cohen's **κ**, WindowDiff, Pk.
The reference scorer ships in this repo:
```bash
python score.py --pred your_preds.json # preds: {stream_id: [0/1 per page]}
```
`score.py` uses `docsplit.eval.metrics.aggregate` (bundled). κ is reported because a degenerate
predict-none/all can look fine on F1 but scores κ ≈ 0 on the sparse cuts. See `SUBMISSION.md` to add a row to
the leaderboard.
`manifest.json` records provenance (per-source stream/page counts, boundary rates, seed).
## License & attribution
CC-BY-SA-4.0 for the our-200 packaging (Nutrient-generated synthetic concatenations). OpenPSS cuts are in
`openpss-mirror` under their upstream terms. TABME++/Tobacco800 are referenced, not redistributed.
## About the author
<a href="https://nutrient.io/">
<img src="https://avatars2.githubusercontent.com/u/1527679?v=3&s=200" height="80" />
</a>
This project is maintained and funded by [Nutrient](https://nutrient.io/) - The #1 PDF SDK library for viewing, editing, eSigning, and more.
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