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README.md

@@ -1,36 +1,175 @@
 ---
 license: cc-by-4.0
+pretty_name: GROBID End-to-End Evaluation Dataset
+language:
+  - en
+size_categories:
+  - 1K<n<10K
+annotations_creators:
+  - expert-generated
+  - machine-generated
+source_datasets:
+  - original
+tags:
+  - grobid
+  - scientific-documents
+  - pdf
+  - pdf-to-xml
+  - tei-xml
+  - jats
+  - nlm
+  - bibliographic-references
+  - document-structure
+  - information-extraction
+  - benchmark
 ---
-# Grobid End 2 End evaluation dataset 
 
-https://grobid.readthedocs.io/en/latest/End-to-end-evaluation/
+# GROBID End-to-End Evaluation Dataset
 
-Official URL: https://zenodo.org/record/7708580
+Reference corpora used for [GROBID](https://github.com/kermitt2/grobid) end-to-end
+benchmarking of scientific-article structuring.
 
------
-
-Here are the datasets used for GROBID end-to-end benchmarking covering:
-
-- metadata extraction,
-
-- bibliographical reference extraction, parsing and citation context identification, and
-
-- full text body structuring.
-
-The following collections are included:
-
-- a PubMedCentral gold-standard dataset called PMC_sample_1943, compiled by Alexandru Constantin. The dataset, around 1.5GB in size, contains 1943 articles from 1943 different journals corresponding to the publications from a 2011 snapshot. For each article, we have a PDF file and a NLM XML file.
+- **Documentation:** https://grobid.readthedocs.io/en/latest/End-to-end-evaluation/
+- **Latest benchmarking scores:** https://grobid.readthedocs.io/en/latest/Benchmarking/
+- **Official archive (Zenodo):** https://zenodo.org/record/7708580
 
-- a bioRxiv dataset called biorxiv-10k-test-2000 of 2000 preprint articles originally compiled with care and published by Daniel Ecer, available on Zenodo. The dataset contains for each article a PDF file and the corresponding reference NLM file (manually created by bioRxiv). The NLM files have been further systematically reviewed and annotated with additional markup corresponding to data and code availability statements and funding statements by the Grobid team. Around 5.4G in size.
-
-- a set of 1000 PLOS articles, called PLOS_1000, randomly selected from the full PLOS Open Access collection. Again, for each article, the published PDF is available with the corresponding publisher JATS XML file, around 1.3GB total size.
-
-- a set of 984 articles from eLife, called eLife_984, randomly selected from their open collection available on GitHub. Every articles come with the published PDF, the publisher JATS XML file and the eLife public HTML file (as bonus, not used), all in their latest version, around 4.5G total.
-
-For each of these datasets, the directory structure is the same and documented here.
-
-Further information on Grobid benchmarking and how to run it: https://grobid.readthedocs.io/en/latest/End-to-end-evaluation/. Latest benchmarking scores are also available in the Grobid documentation: https://grobid.readthedocs.io/en/latest/Benchmarking/
-
-These resources are originally published under CC-BY license. Our additional annotations are similarly under CC-BY.
+-----
 
-We thank NIH, bioRxiv, PLOS and eLife for making these resources Open Access and reusable.
+## Dataset summary
+
+These are the datasets used for GROBID end-to-end benchmarking, covering:
+
+- **metadata extraction** (title, authors, affiliations, abstract, …),
+- **bibliographical reference** extraction, parsing and citation-context
+  identification, and
+- **full-text body** structuring.
+
+Each collection pairs published PDFs with a gold/reference XML (JATS or NLM) that
+GROBID's output is scored against. In total the dataset contains **~5,927 articles**
+across four collections (~15 GB).
+
+## Collections
+
+- **`PMC_sample_1943`** — a PubMedCentral gold-standard dataset compiled by Alexandru
+  Constantin, ~1.5 GB, 1943 articles from 1943 different journals (a 2011 snapshot of
+  the PMC Open Access Subset). Each article ships a PDF, an NLM XML file, and a PDFX
+  v1.9 conversion. See `PMC_sample_1943/__README__` for provenance.
+
+- **`biorxiv-10k-test-2000`** — 2000 bioRxiv preprint articles, originally compiled and
+  published by Daniel Ecer on Zenodo, ~5.4 GB. Each article ships a PDF and the
+  corresponding reference NLM file (created by bioRxiv). The NLM files were further
+  systematically reviewed by the GROBID team and annotated with additional markup for
+  the four statement types described in
+  [Statement-level annotations](#statement-level-annotations) below.
+
+- **`PLOS_1000`** — 1000 PLOS articles randomly selected from the full PLOS Open Access
+  collection, ~1.3 GB. Each article ships the published PDF and the corresponding
+  publisher **JATS** XML file. A `PLOS_1000/download.sh` script records the original PDF
+  source URLs.
+
+- **`eLife_984`** — 984 articles randomly selected from the eLife open collection on
+  GitHub, ~4.5 GB. Each article ships the published PDF, the publisher **JATS** XML
+  file, and the eLife public HTML file (included as a bonus; not used in scoring), all
+  in their latest version.
+
+## Dataset structure
+
+Every collection is a directory of one sub-directory per article. The file naming
+differs slightly per source:
+
+```
+grobid-evaluation-hf/
+├── PMC_sample_1943/
+│   ├── __README__                       # provenance (Constantin, PDFX)
+│   └── <Journal_Year_.../>              # one folder per article
+│       ├── <id>.pdf                     # published PDF
+│       ├── <id>.nxml                    # NLM reference XML (gold)
+│       └── <id>.pdfx.xml                # PDFX v1.9 conversion
+├── biorxiv-10k-test-2000/
+│   └── <id>v<n>/                        # e.g. 002485v1
+│       ├── <id>v<n>.pdf
+│       └── <id>v<n>.xml                 # NLM reference XML (Grobid-team enriched)
+├── PLOS_1000/
+│   ├── download.sh                      # original PDF download URLs
+│   └── <id>/                            # e.g. pbio.0020278
+│       ├── <id>.pdf
+│       └── journal.<id>.xml             # JATS reference XML (gold)
+└── eLife_984/
+    └── <id>/                            # e.g. 00013
+        ├── elife-<id>-v<n>.pdf
+        ├── elife-<id>-v<n>.xml          # JATS reference XML (gold)
+        └── elife-<id>-v<n>.html         # bonus, not used in scoring
+```
+
+## Statement-level annotations
+
+Beyond the publisher-provided body structure, the GROBID end-to-end evaluation scores
+four "statement" fields extracted from the article back matter. Where the source XML
+tags them inconsistently (or not at all), the GROBID team harmonised / added the markup
+— most notably on the bioRxiv NLM files (systematically reviewed and annotated) and via
+a disambiguating `type="contribution"` attribute on PLOS JATS, where `fn-type="con"` is
+reused for both conflict-of-interest and author-contribution footnotes.
+
+| Statement | Reference-XML markup recognised | Notes |
+|---|---|---|
+| **Data / code availability** | `//sec[@sec-type="availability"]`, `//p[@content-type="availability"]`, `//sec[@sec-type="data-availability"]` (eLife), `//custom-meta[@id="data-availability"]` (PLOS) | |
+| **Funding** | `//sec[@sec-type="funding"]`, `//p[@content-type="funding"]`, `//funding-statement` (PLOS) | |
+| **Conflict / competing interests** | `//fn[@fn-type="conflict"]`, `//fn-group[@content-type="competing-interest"]`, `//fn[@fn-type="COI"]`, `//sec[@sec-type="COI-statement"]` | |
+| **Author contributions** | `//fn[@type="contribution"]` (team-added disambiguation), `//fn-group[@content-type="author-contribution"]`, `//sec[@sec-type="contribution"]` | a.k.a. CRediT / author contributions |
+
+These correspond to GROBID's `availability_stmt`, `funding_stmt`, `conflict_stmt` and
+`contribution_stmt` evaluation fields. Not every article contains every statement; the
+markup is present only where the corresponding statement exists in the source article.
+
+## How to use
+
+This dataset is a file tree of PDFs and reference XML — it is **not** a tabular dataset,
+so use `huggingface_hub` to download it rather than `datasets.load_dataset`:
+
+```python
+from huggingface_hub import snapshot_download
+
+path = snapshot_download(
+    repo_id="<owner>/grobid-evaluation",   # replace with the actual repo id
+    repo_type="dataset",
+    allow_patterns=["PLOS_1000/*"],        # optional: fetch one collection
+)
+```
+
+Point GROBID's end-to-end evaluation at the downloaded collection following
+https://grobid.readthedocs.io/en/latest/End-to-end-evaluation/.
+
+## Licensing
+
+These resources are originally published under the CC-BY license. The additional
+annotations contributed by the GROBID team (data/code-availability and funding markup
+on the bioRxiv set) are similarly released under **CC-BY 4.0**.
+
+We thank NIH/PMC, bioRxiv, PLOS and eLife for making these resources Open Access and
+reusable.
+
+## Citation
+
+If you use this dataset, please cite the GROBID end-to-end benchmark archive:
+
+```bibtex
+@dataset{grobid_end_to_end_evaluation,
+  title  = {GROBID end-to-end evaluation datasets},
+  author = {GROBID team},
+  year   = {2023},
+  url    = {https://zenodo.org/record/7708580},
+  note   = {https://grobid.readthedocs.io/en/latest/End-to-end-evaluation/}
+}
+```
+
+The PMC sample additionally derives from:
+
+```bibtex
+@inproceedings{constantin2013pdfx,
+  title     = {PDFX: fully-automated PDF-to-XML conversion of scientific literature},
+  author    = {Constantin, Alexandru and Pettifer, Steve and Voronkov, Andrei},
+  booktitle = {Proceedings of the 2013 ACM Symposium on Document Engineering},
+  year      = {2013},
+  publisher = {ACM}
+}
+```