Add document-level sample of PDFluent layout ground truth

.gitattributes

@@ -58,3 +58,178 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+pretty_name: PDFluent PDF Document Layout Ground Truth (sample)
+license: other
+license_name: mixed-per-config
+license_link: https://huggingface.co/datasets/PDFluent/pdf-document-layout-ground-truth#licences-and-attribution
+language:
+  - en
+size_categories:
+  - 1K<n<10K
+task_categories:
+  - object-detection
+  - image-to-text
+tags:
+  - pdf
+  - document-ai
+  - document-understanding
+  - layout-analysis
+  - table-extraction
+  - heading-detection
+  - math-formula-recognition
+  - latex
+  - ocr
+  - rag
+  - ground-truth
+configs:
+  - config_name: default
+    default: true
+    data_files:
+      - split: train
+        path: data/default/train.jsonl
+  - config_name: third_party_scans
+    data_files:
+      - split: train
+        path: data/third_party_scans/train.jsonl
+  - config_name: share_alike
+    data_files:
+      - split: train
+        path: data/share_alike/train.jsonl
+---
+
+# PDFluent PDF document layout ground truth (document-level sample)
+
+A document-level sample of PDFluent's ground truth for PDF structure extraction: pages with layout annotations, formulas and scans, for researchers building document AI tools.
+
+## What is in it
+
+The dataset has three configs. `default`: born-digital PDF pages with block-level layout annotations (headings, paragraphs, tables) and display-formula LaTeX. `third_party_scans`: scan pages from FinTabNet, with IBM's ground truth. `share_alike`: pages from CC BY-SA papers, with annotations under CC BY-SA.
+
+## Quick start
+
+```python
+import json
+from datasets import load_dataset
+
+repo = "PDFluent/pdf-document-layout-ground-truth"
+pages = load_dataset(repo, "default", split="train").filter(lambda r: r["kind"] == "page")
+formulas = load_dataset(repo, "default", split="train").filter(lambda r: r["kind"] == "formula")
+scans = load_dataset(repo, "third_party_scans", split="train")
+sa = load_dataset(repo, "share_alike", split="train")
+
+row = pages[0]
+annotation = json.loads(row["annotation_json"])
+print(row["document_id"], row["page_number"], list(annotation))
+```
+
+The PDF behind each row is in this repository at the path in `asset`:
+
+```python
+from huggingface_hub import hf_hub_download
+
+pdf_path = hf_hub_download(repo, row["asset"], repo_type="dataset")
+```
+
+## Fields
+
+Each row links to a PDF page asset by SHA-256. annotation_json is a string because page, scan and formula ground truth schemas differ.
+
+| Field | Meaning |
+|---|---|
+| `document_id` | Source document identifier (for example `arxiv:...`) |
+| `source` | Source collection |
+| `kind` | `page`, `formula` or `scan` |
+| `page_number` | Page in the source document |
+| `asset`, `asset_sha256` | Path of the PDF file in this repo and its SHA-256 |
+| `annotation_json` | Ground truth as a JSON string (blocks, boxes, reading order, source text, LaTeX) |
+| `annotation_licence`, `annotation_attribution` | Licence and credit for the annotation |
+| `paper_licence`, `paper_attribution_json` | Licence and attribution of the underlying paper |
+
+There is one split, `train`. There is no evaluation split.
+
+## Sampling
+
+This is a sample, not the full ground truth. Documents were selected at document level, stratified by source. The sample supports evaluation and light fine-tuning but is too small to train a model to PDFluent's level.
+
+## Holdouts and label quality
+
+Documents in PDFluent's benchmark and holdout sets are excluded. The exclusion registry has partial coverage for some sources. Labels are generated automatically and inherit extraction errors.
+
+## Licences and attribution
+
+Our annotations in `default` are CC BY 4.0: credit 'Innovation Trigger B.V., PDFluent ground-truth annotations (2026)' and link to https://pdfluent.com. Paper content keeps its original licence. `third_party_scans` keeps CDLA-Permissive-1.0. `share_alike` annotations are CC BY-SA 4.0.
+
+| Config | Annotation licence | Underlying content |
+|---|---|---|
+| `default` | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) | arXiv (CC BY 4.0, CC0 1.0), PubMed Central (CC BY), synthetic pages |
+| `third_party_scans` | [CDLA-Permissive-1.0](https://cdla.dev/permissive-1-0/) | FinTabNet, IBM Research |
+| `share_alike` | [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/) | arXiv papers under CC BY-SA 4.0 |
+
+Mandatory credit for `default`: **Innovation Trigger B.V., PDFluent ground-truth annotations (2026)**, https://pdfluent.com. Keep the credit, the licence link and an indication of your changes. Per-document paper credit is in [ATTRIBUTION.tsv](ATTRIBUTION.tsv). The package as a whole is mixed-source and has no blanket licence; check the config you use.
+
+## Citation
+
+```bibtex
+@misc{pdfluent_layout_ground_truth_2026,
+  author       = {{Innovation Trigger B.V.}},
+  title        = {PDFluent PDF document layout ground truth (document-level sample)},
+  year         = {2026},
+  publisher    = {Hugging Face},
+  url          = {https://huggingface.co/datasets/PDFluent/pdf-document-layout-ground-truth},
+  note         = {PDFluent, https://pdfluent.com}
+}
+```
+
+## Links
+
+- Website: https://pdfluent.com
+- Documentation: https://pdfluent.com/docs
+- Licence: https://pdfluent.com/license
+- SDK source and releases: https://github.com/pdfluent/pdfluent-sdk
+- Organisation: https://huggingface.co/PDFluent
+- Formula recognition model: https://huggingface.co/PDFluent/formula-recognition-onnx
+- Heading level classifier: https://huggingface.co/PDFluent/pdf-heading-level-classifier
+- Layout ground-truth sample: https://huggingface.co/datasets/PDFluent/pdf-document-layout-ground-truth

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