README.md

metadata

license: cc-by-4.0
language: en
task_categories:
  - text-classification
  - question-answering
  - text-retrieval

DefExtra

Overview

DefExtra contains 268 definition records (term, definition, context, type) from 75 papers. We do not ship excerpts from papers due to copyright. Instead, we ship markers and scripts that let users hydrate the dataset from their own PDFs.

Why this workflow:

• We cannot redistribute copyrighted excerpts.
• We therefore ship only localization markers plus scripts to reconstruct the text from user‑supplied PDFs.

Examples (from our own papers; after hydration)

Source	Concept	Definition	Context (excerpt)
https://aclanthology.org/2024.lrec-main.952	media bias	“a skewed portrayal of information favoring certain group interests, which manifests in multiple facets, including political, gender, racial, and linguistic biases.”	“Media bias is a skewed portrayal of information favoring certain group interests … Such subtypes of bias … make the classification of media bias a challenging task.”
https://arxiv.org/abs/2312.16148	spin bias	“a form of bias introduced either by leaving out necessary information or by adding unnecessary information.”	“Spin Bias describes a form of bias introduced either by leaving out necessary information … or by adding unnecessary information.”

Quickstart (DefExtra hydration)

1. Put PDFs in pdfs/ (filename should match paper_id, DOI/PII alias, or arXiv ID).
2. Start a GROBID server (see docs/defextra_hydration.md).
3. Hydrate:

uv run python scripts/hydrate_defextra.py \
  --legal-csv data/defextra_legal.csv \
  --pdf-dir pdfs \
  --grobid-out grobid_out \
  --output-csv defextra_hydrated.csv \
  --report defextra_hydrated_report.txt \
  --require-complete

Getting PDFs

• See docs/get_pdfs.md for sources and a helper script that lists required PDFs.
• defextra_required_pdfs.csv and defextra_required_pdfs.md are precomputed lists.

Environment (uv)

• This repo ships a pyproject.toml with all dependencies.
• Run any script with uv run python ... and uv will resolve/install deps.

Data files

• data/defextra_legal.csv / data/defextra_legal.parquet: DefExtra markers (no excerpts).

Hydrated columns

The hydrated output (e.g., defextra_hydrated.csv) matches the schema below. Full legal marker columns are documented in docs/defextra_hydration.md.

Column	Description
paper_id	Paper identifier (often a Semantic Scholar ID, DOI, or arXiv ID).
paper_title	Paper title.
paper_doi	DOI (if available).
paper_arxiv	arXiv ID or URL (if available).
concept	Term / concept being defined.
definition	Definition text (hydrated from PDFs).
context	Context excerpt (hydrated from PDFs).
definition_type	Definition type (e.g., explicit / implicit).
source_file	Source JSON filename used during curation.
is_out_of_domain	Boolean flag for out‑of‑domain papers.

Scripts

• scripts/hydrate_defextra.py: hydrate DefExtra from PDFs + GROBID.
• scripts/pdf_to_grobid.py: batch GROBID runner (requires a running GROBID server).
• scripts/list_defextra_pdfs.py: list required PDFs + download links.
• scripts/build_defextra_test_pdfs.py: build a test PDF set from a larger PDF pool.
• scripts/report_defextra_status.py: summarize missing items by paper/definition.

Documentation

• docs/defextra_hydration.md (technical details, CLI flags, markers).
• docs/get_pdfs.md (how to find PDFs).
• docs/mismatch_examples.md (mismatch types with short excerpts).

Expected minor mismatches

• Small differences vs. the manual reference can occur due to PDF/GROBID text normalization.
• Typical cases: line‑break hyphenation, spacing around numbers, citation formatting.
• These are documented and do not affect the ability to hydrate all entries.

Notes

• Hash IDs are typically Semantic Scholar paper IDs; many PDFs can be obtained from Semantic Scholar.
• If you see PDF hash mismatch warnings, verify you have the correct paper version and rerun with --allow-pdf-hash-mismatch only after manual inspection.
• The script was largely produced using LLMs for robustness.

Citation

@misc{kucera2026scidefautomatingdefinitionextraction,
      title={SciDef: Automating Definition Extraction from Academic Literature with Large Language Models}, 
      author={Filip Ku\v{c}era and Christoph Mandl and Isao Echizen and Radu Timofte and Timo Spinde},
      year={2026},
      eprint={2602.05413},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2602.05413}, 
}