Datasets:
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 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
- 🎯 Demo: doc-split-demo
- 🟢 Model: doc-split-mini-e5 (open weights)
- 🌍 OpenPSS cuts: 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 | Dutch; sparse- & dense-boundary regimes |
| TABME++ / Tobacco800 | upstream (not redistributed) | reported for reference; licenses/gating prevent re-hosting |
Load
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:
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
This project is maintained and funded by Nutrient - The #1 PDF SDK library for viewing, editing, eSigning, and more.