Upload folder using huggingface_hub

.gitignore

@@ -0,0 +1,4 @@
+.venv
+__pycache__
+outputs/
+grobid_out/

README.md

@@ -4,22 +4,35 @@ 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 legal markers and scripts that let users hydrate the dataset from their own PDFs.
 
-Why this workflow
+Why this workflow:
+
 - We cannot redistribute copyrighted excerpts.
 - We therefore ship **only localization markers** plus scripts to reconstruct the text from user‑supplied PDFs.
 
-Quickstart (DefExtra hydration)
+## Examples (from our own papers; after hydration)
+
+| Source | Concept | Definition | Context (excerpt) |
+| --- | --- | --- | --- |
+| [https://aclanthology.org/2024.lrec-main.952](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](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:
-```sh
-python scripts/hydrate_defextra.py \
+
+```bash
+uv run python scripts/hydrate_defextra.py \
   --legal-csv data/defextra_legal.csv \
   --pdf-dir pdfs \
   --grobid-out grobid_out \
@@ -28,24 +41,41 @@ python scripts/hydrate_defextra.py \
   --require-complete
 ```
 
-Getting PDFs
-- See [`docs/get_pdfs.md`](docs/get_pdfs.md) for sources and a helper script that lists required PDFs.
+## 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 files
 - `data/defextra_legal.csv` / `data/defextra_legal.parquet`: DefExtra markers (no excerpts).
 
-Scripts
+## 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.
-- `scripts/compare_defextra_csvs.py`: compare hydrated output to a reference.
 
-Documentation
-- `docs/defextra_hydration.md` (technical details, CLI flags, markers).
-- `docs/get_pdfs.md` (how to find PDFs).
+## Documentation
+
+- [`docs/defextra_hydration.md`](docs/defextra_hydration.md) (technical details, CLI flags, markers).
+- [`docs/get_pdfs.md`](docs/get_pdfs.md) (how to find PDFs).
+- See [`docs/defextra_hydration.md`](docs/defextra_hydration.md) for technical details and [`docs/get_pdfs.md`](docs/get_pdfs.md) for PDF sources.
+
+## 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
 
-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.

defextra_required_pdfs.csv

@@ -0,0 +1,76 @@
+paper_id,normalized_id,paper_title,paper_doi,paper_arxiv,preferred_pdf_name,alias_pdf_names,url_semanticscholar,url_doi,url_arxiv,url_acl
+0090023afc66cd2741568599057f4e82b566137c,0090023afc66cd2741568599057f4e82b566137c,A Survey on Bias and Fairness in Machine Learning,,1908.09635v3,0090023afc66cd2741568599057f4e82b566137c.pdf,,https://www.semanticscholar.org/paper/0090023afc66cd2741568599057f4e82b566137c,,https://arxiv.org/abs/1908.09635v3,
+016f7a076ac272db106fbcea056752c7307f676a,016f7a076ac272db106fbcea056752c7307f676a,Racial and Ethnic Disparities in Crime and Criminal Justice in the United States,10.1086/449253,,016f7a076ac272db106fbcea056752c7307f676a.pdf,,https://www.semanticscholar.org/paper/016f7a076ac272db106fbcea056752c7307f676a,https://doi.org/10.1086/449253,,
+0209e602acaeab882fee84e244caf574cf345ef9,0209e602acaeab882fee84e244caf574cf345ef9,How numeracy influences risk comprehension and medical decision making.,10.1037/a0017327,,0209e602acaeab882fee84e244caf574cf345ef9.pdf,,https://www.semanticscholar.org/paper/0209e602acaeab882fee84e244caf574cf345ef9,https://doi.org/10.1037/a0017327,,
+033b21cf1c6d3bdae587e673452b994443bf3546,033b21cf1c6d3bdae587e673452b994443bf3546,Defining narrative,10.1017/cbo9780511816932.004,,033b21cf1c6d3bdae587e673452b994443bf3546.pdf,,https://www.semanticscholar.org/paper/033b21cf1c6d3bdae587e673452b994443bf3546,https://doi.org/10.1017/cbo9780511816932.004,,
+03c4bb2121b3dd2b5302d37c81e84092a501bc91,03c4bb2121b3dd2b5302d37c81e84092a501bc91,"Platformed racism: the mediation and circulation of an Australian race-based controversy on Twitter, Facebook and YouTube",10.1080/1369118x.2017.1293130,,03c4bb2121b3dd2b5302d37c81e84092a501bc91.pdf,,https://www.semanticscholar.org/paper/03c4bb2121b3dd2b5302d37c81e84092a501bc91,https://doi.org/10.1080/1369118x.2017.1293130,,
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+1538c4777271ae6abb542801dac01423f4d566ad,1538c4777271ae6abb542801dac01423f4d566ad,Understanding the Role and Methods of Meta-Analysis in IS Research,10.17705/1cais.01632,,1538c4777271ae6abb542801dac01423f4d566ad.pdf,,https://www.semanticscholar.org/paper/1538c4777271ae6abb542801dac01423f4d566ad,https://doi.org/10.17705/1cais.01632,,
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+17734113f254a64b3bae312713edba3b1e34fb56,17734113f254a64b3bae312713edba3b1e34fb56,The Emergence of Deepfake Technology: A Review,,,17734113f254a64b3bae312713edba3b1e34fb56.pdf,,https://www.semanticscholar.org/paper/17734113f254a64b3bae312713edba3b1e34fb56,,,
+1901.00596v4,1901.00596v4,A Comprehensive Survey on Graph Neural Networks,,1901.00596v4,1901.00596v4.pdf,,,,https://arxiv.org/abs/1901.00596v4,
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+1ccc69b50a7495af1547833415f89536619c93e9,1ccc69b50a7495af1547833415f89536619c93e9,The Dynamics of Public Attention: Agenda-Setting Theory Meets Big Data,10.1111/jcom.12088,,1ccc69b50a7495af1547833415f89536619c93e9.pdf,,https://www.semanticscholar.org/paper/1ccc69b50a7495af1547833415f89536619c93e9,https://doi.org/10.1111/jcom.12088,,
+2025.acl-long.1513,2025.acl-long.1513,"PolyNarrative: A Multilingual, Multilabel, Multi-domain Dataset for Narrative Extraction from News Articles",,,2025.acl-long.1513.pdf,,,,,
+2106.04554v2,2106.04554v2,A Survey of Transformers,,2106.04554v2,2106.04554v2.pdf,,,,https://arxiv.org/abs/2106.04554v2,
+2106.16117v1,2106.16117v1,"ENERGY SECURITY: KEY CONCEPTS, COMPONENTS, AND CHANGE OF THE PARADIGM",,,2106.16117v1.pdf,,,,,
+22170e94588cf3b970ff8855c946a130aaa065c2,22170e94588cf3b970ff8855c946a130aaa065c2,Explaining Bargaining Impasse: The Role of Self-Serving Biases,,,22170e94588cf3b970ff8855c946a130aaa065c2.pdf,,https://www.semanticscholar.org/paper/22170e94588cf3b970ff8855c946a130aaa065c2,,,
+22cb049f711570de72ea60a5f6b49fdf4459d589,22cb049f711570de72ea60a5f6b49fdf4459d589,"""From Protest to Agenda-Building: Description Bias in Media Coverage of Protest Events in Washington, D.C.""",,,22cb049f711570de72ea60a5f6b49fdf4459d589.pdf,,https://www.semanticscholar.org/paper/22cb049f711570de72ea60a5f6b49fdf4459d589,,,
+2303.14725v2,2303.14725v2,"Natural Language Reasoning, A Survey",10.1145/nnnnnnn.nnnnnnn,2303.14725v2,2303.14725v2.pdf,,,https://doi.org/10.1145/nnnnnnn.nnnnnnn,https://arxiv.org/abs/2303.14725v2,
+235c4f33d5bfc81bfa09a2458fcc0e42ef4454dc,235c4f33d5bfc81bfa09a2458fcc0e42ef4454dc,Understanding Propaganda: The Epistemic Merit Model and Its Application to Art Author(s),,,235c4f33d5bfc81bfa09a2458fcc0e42ef4454dc.pdf,,https://www.semanticscholar.org/paper/235c4f33d5bfc81bfa09a2458fcc0e42ef4454dc,,,
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+264c3ad2d861782583e41130677fb6d7856f9dc3,264c3ad2d861782583e41130677fb6d7856f9dc3,Mandatory Non-financial Disclosure and Its Influence on CSR: An International Comparison,10.1007/s10551-019-04200-0,,264c3ad2d861782583e41130677fb6d7856f9dc3.pdf,,https://www.semanticscholar.org/paper/264c3ad2d861782583e41130677fb6d7856f9dc3,https://doi.org/10.1007/s10551-019-04200-0,,
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+3457607,3457607,A Survey on Bias and Fairness in Machine Learning,10.1145/3457607,,3457607.pdf,,,https://doi.org/10.1145/3457607,,
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+4b33419863b96c270d5875af9bd5af3ce5dbb1e2,4b33419863b96c270d5875af9bd5af3ce5dbb1e2,The Social Amplification of Risk A Conceptual Framework,,,4b33419863b96c270d5875af9bd5af3ce5dbb1e2.pdf,,https://www.semanticscholar.org/paper/4b33419863b96c270d5875af9bd5af3ce5dbb1e2,,,
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+4eb5a9745dfc892cb42ed427a5f08e6abf8df7e3,4eb5a9745dfc892cb42ed427a5f08e6abf8df7e3,"Affective polarization, local contexts and public opinion in America",10.1038/s41562-020-01012-5,,4eb5a9745dfc892cb42ed427a5f08e6abf8df7e3.pdf,,https://www.semanticscholar.org/paper/4eb5a9745dfc892cb42ed427a5f08e6abf8df7e3,https://doi.org/10.1038/s41562-020-01012-5,,
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+Rosen_gjcpi_2018_3,Rosen_gjcpi_2018_3,"Issues, Concepts and Applications for Sustainability",10.12893/gjcpi.2018.3.4,,Rosen_gjcpi_2018_3.pdf,,,https://doi.org/10.12893/gjcpi.2018.3.4,,
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+c84a169e6df175c4662012d3ba7dbf8fa1b5abc9,c84a169e6df175c4662012d3ba7dbf8fa1b5abc9,‘Fake news’ is the invention of a liar: How false information circulates within the hybrid news system,10.1177/0011392119837536,,c84a169e6df175c4662012d3ba7dbf8fa1b5abc9.pdf,,https://www.semanticscholar.org/paper/c84a169e6df175c4662012d3ba7dbf8fa1b5abc9,https://doi.org/10.1177/0011392119837536,,
+daw084,daw084,Just a subtle difference? Findings from a systematic review on definitions of nutrition literacy and food literacy,10.1093/heapro/daw084,,daw084.pdf,,,https://doi.org/10.1093/heapro/daw084,,
+doi:10.1145/3677092,3677092,,,,3677092.pdf,,,,,
+dx.doi.org/https://doi.org/10.1016/j.ipm.2021.102505,j.ipm.2021.102505,,,,j.ipm.2021.102505.pdf,S0306457321000157.pdf;1-s2.0-S0306457321000157-main.pdf;S0957417423021437.pdf;1-s2.0-S0957417423021437-main.pdf;S0306457321000157.pdf;1-s2.0-S0306457321000157-main.pdf;S0957417423021437.pdf;1-s2.0-S0957417423021437-main.pdf,,https://doi.org/dx.doi.org/https://doi.org/10.1016/j.ipm.2021.102505,,
+eb29476dd81aefedf2896db42f039f003a0ec5bf,eb29476dd81aefedf2896db42f039f003a0ec5bf,Organic or Local? Investigating Consumer Preference for Fresh Produce Using a Choice Experiment with Real Economic Incentives,,,eb29476dd81aefedf2896db42f039f003a0ec5bf.pdf,,https://www.semanticscholar.org/paper/eb29476dd81aefedf2896db42f039f003a0ec5bf,,,
+frai-06-1225093,frai-06-1225093,Rationalization for explainable NLP: a survey,,,frai-06-1225093.pdf,,,,,
+https://aclanthology.org/2021.findings-emnlp.101,2021.findings-emnlp.101,,,,2021.findings-emnlp.101.pdf,,,,,https://aclanthology.org/2021.findings-emnlp.101
+https://aclanthology.org/2024.lrec-main.952,2024.lrec-main.952,,,,2024.lrec-main.952.pdf,,,,,https://aclanthology.org/2024.lrec-main.952
+https://arxiv.org/abs/2312.16148,2312.16148,,,,2312.16148.pdf,,,,,
+https://link.springer.com/article/10.1007/s00799-018-0261-y,s00799-018-0261-y,,,,s00799-018-0261-y.pdf,,,,,
+https://media-bias-research.org/wp-content/uploads/2024/07/Preprint_ICWSM_25_NewsUnfold,Preprint_ICWSM_25_NewsUnfold,,,,Preprint_ICWSM_25_NewsUnfold.pdf,,,,,
+https://www.sciencedirect.com/science/article/pii/S0957417423021437,S0957417423021437,,,,S0957417423021437.pdf,,,,,
+icomputing.0124,icomputing.0124,A Survey of Task Planning with Large Language Models,10.34133/icomputing.0124,,icomputing.0124.pdf,,,https://doi.org/10.34133/icomputing.0124,,
+s10462-022-10338-7,s10462-022-10338-7,A survey on narrative extraction from textual data,10.1007/s10462-022-10338-7,,s10462-022-10338-7.pdf,,,https://doi.org/10.1007/s10462-022-10338-7,,
+s10816-016-9274-2,s10816-016-9274-2,Quality Assurance in Archaeological Survey,10.1007/s10816-016-9274-2,,s10816-016-9274-2.pdf,,,https://doi.org/10.1007/s10816-016-9274-2,,
+s40537-025-01077-x,s40537-025-01077-x,Survey on terminology extraction from texts,10.1186/s40537-025-01077-x,,s40537-025-01077-x.pdf,,,https://doi.org/10.1186/s40537-025-01077-x,,

defextra_required_pdfs.md

@@ -0,0 +1,77 @@
+# DefExtra required PDFs
+
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+- 2106.04554v2 — A Survey of Transformers (https://arxiv.org/abs/2106.04554v2)
+- 2106.16117v1 — ENERGY SECURITY: KEY CONCEPTS, COMPONENTS, AND CHANGE OF THE PARADIGM
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+- 3584741 — A Survey on Event-Based News Narrative Extraction (https://doi.org/10.1145/3584741)
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+- Rosen_gjcpi_2018_3 — Issues, Concepts and Applications for Sustainability (https://doi.org/10.12893/gjcpi.2018.3.4)
+- Survey_on_terminology_extraction_from_texts — Survey on terminology extraction from texts (https://doi.org/10.1186/s40537-025-01077-x)
+- a7b52fa3ff2606013a6ab9ba294743d7de637e6a — Examining the Impact of Structural Racism on Food Insecurity (https://www.semanticscholar.org/paper/a7b52fa3ff2606013a6ab9ba294743d7de637e6a, https://doi.org/10.1097/fch.0000000000000183)
+- bff1326ea0f792e3557fc8ad0731733ba7f8b091 — PRIOR ALLIANCES WITH TARGETS AND ACQUISITION PERFORMANCE IN KNOWLEDGE-INTENSIVE INDUSTRIES (https://www.semanticscholar.org/paper/bff1326ea0f792e3557fc8ad0731733ba7f8b091, https://doi.org/10.1287/orsc.1100.0528)
+- c1e92f1be2387d14dcfaa5e1640a9939724a312a — TITLE: An empirical examination of echo chambers in US climate policy networks (https://www.semanticscholar.org/paper/c1e92f1be2387d14dcfaa5e1640a9939724a312a)
+- c84a169e6df175c4662012d3ba7dbf8fa1b5abc9 — ‘Fake news’ is the invention of a liar: How false information circulates within the hybrid news system (https://www.semanticscholar.org/paper/c84a169e6df175c4662012d3ba7dbf8fa1b5abc9, https://doi.org/10.1177/0011392119837536)
+- daw084 — Just a subtle difference? Findings from a systematic review on definitions of nutrition literacy and food literacy (https://doi.org/10.1093/heapro/daw084)
+- doi:10.1145/3677092 — 
+- dx.doi.org/https://doi.org/10.1016/j.ipm.2021.102505 —  (https://doi.org/dx.doi.org/https://doi.org/10.1016/j.ipm.2021.102505)
+- eb29476dd81aefedf2896db42f039f003a0ec5bf — Organic or Local? Investigating Consumer Preference for Fresh Produce Using a Choice Experiment with Real Economic Incentives (https://www.semanticscholar.org/paper/eb29476dd81aefedf2896db42f039f003a0ec5bf)
+- frai-06-1225093 — Rationalization for explainable NLP: a survey
+- https://aclanthology.org/2021.findings-emnlp.101 —  (https://aclanthology.org/2021.findings-emnlp.101)
+- https://aclanthology.org/2024.lrec-main.952 —  (https://aclanthology.org/2024.lrec-main.952)
+- https://arxiv.org/abs/2312.16148 — 
+- https://link.springer.com/article/10.1007/s00799-018-0261-y — 
+- https://media-bias-research.org/wp-content/uploads/2024/07/Preprint_ICWSM_25_NewsUnfold — 
+- https://www.sciencedirect.com/science/article/pii/S0957417423021437 — 
+- icomputing.0124 — A Survey of Task Planning with Large Language Models (https://doi.org/10.34133/icomputing.0124)
+- s10462-022-10338-7 — A survey on narrative extraction from textual data (https://doi.org/10.1007/s10462-022-10338-7)
+- s10816-016-9274-2 — Quality Assurance in Archaeological Survey (https://doi.org/10.1007/s10816-016-9274-2)
+- s40537-025-01077-x — Survey on terminology extraction from texts (https://doi.org/10.1186/s40537-025-01077-x)

docs/defextra_hydration.md

@@ -1,35 +1,44 @@
-# DefExtra hydration (technical)
+# DefExtra hydration
+
+## Overview
 
 This dataset cannot ship excerpts. We ship markers only. Users supply PDFs and run hydration to reconstruct the definitions and contexts.
 
-```mermaid
-flowchart LR
-  A[data/defextra_legal.csv] --> B[hydrate_defextra.py]
-  B --> C[defextra_hydrated.csv]
-  subgraph GROBID
-    D[pdf_to_grobid.py] --> E[*.grobid.tei.xml]
-  end
-  B --> E
-```
+See [`README.md`](../README.md) for the high‑level overview and examples.
 
 ## Requirements
+
 - Python 3.10+
 - A running GROBID server (default: `http://localhost:8070`).
+
   Example Docker run:
-  ```
+
+  ```bash
   docker run --rm -p 8070:8070 grobid/grobid:0.8.0
   ```
+
 - Python packages used by scripts:
   - `grobid-client-python`, `lxml`, `pdfplumber`, `pdfminer.six`, `PyPDF2`, `pyarrow`
 
+## UV usage
+
+This repo ships a `pyproject.toml`, so you can run:
+
+```bash
+uv run python scripts/hydrate_defextra.py ...
+```
+
 ## Getting PDFs
+
 See `docs/get_pdfs.md` for sources and a helper script that lists required PDFs.
 
-## Quickstart
+## Quickstart (run GROBID)
+
 1) Place your PDFs in `pdfs/`.
 2) Hydrate (runs GROBID unless `--skip-grobid`):
-```
-python scripts/hydrate_defextra.py \
+
+```bash
+uv run python scripts/hydrate_defextra.py \
   --legal-csv data/defextra_legal.csv \
   --pdf-dir pdfs \
   --grobid-out grobid_out \
@@ -38,21 +47,63 @@ python scripts/hydrate_defextra.py \
   --require-complete
 ```
 
+## Quickstart (skip GROBID, use existing TEI)
+
+If you already have TEI XML files (e.g., produced by your own GROBID run), point
+`--grobid-out` to that TEI folder and add `--skip-grobid`:
+
+```bash
+uv run python scripts/hydrate_defextra.py \
+  --legal-csv data/defextra_legal.csv \
+  --pdf-dir pdfs \
+  --grobid-out /path/to/tei_xml_dir \
+  --output-csv defextra_hydrated.csv \
+  --report defextra_hydrated_report.txt \
+  --require-complete \
+  --skip-grobid
+```
+
 ## File naming expectations
+
 - Preferred: `<paper_id>.pdf` (the `paper_id` in the CSV).
 - DOI/arXiv/PII aliases are supported for common cases.
 - Hash IDs are often Semantic Scholar IDs; many PDFs can be downloaded from there.
 
 ## GROBID configuration
-- By default, `scripts/pdf_to_grobid.py` will generate a temporary config that points to `http://localhost:8070`.
+
+- By default, `scripts/pdf_to_grobid.py` generates a temporary config that points to `http://localhost:8070`.
 - Use `--grobid-config config.json` to override the URL/timeout/batch size.
 
 ## Hash mismatch behavior
+
 - The legal CSV includes hash markers to verify that the PDF content matches the paper version.
 - Default: **skip** PDFs with hash mismatches and report them.
 - Optional: `--allow-pdf-hash-mismatch` to continue anyway (use only after manual inspection).
 
+## Interpretation of warnings
+
+- `Error initializing GROBID client` or `GROBID server ... does not appear up and running`:
+  GROBID is not reachable. Start the server (or Docker) or pass `--grobid-config` with the correct URL. If you already have TEI files, rerun with `--skip-grobid`.
+
+- `Processing failed ... [BAD_INPUT_DATA] ... error code: 139` or `pdfalto` errors:
+  GROBID could not parse a PDF (often a damaged or unusual file). Hydration may still succeed via PDF text fallback, but TEI will be missing. Try a different PDF version.
+
+- `Warning: PDF hash markers did not match ... skipping PDF`:
+  The PDF content differs from the expected version. Replace the PDF with the correct version or rerun with `--allow-pdf-hash-mismatch` and manually inspect outputs.
+
+- `Warning: PDF text extraction failed ...`:
+  The PDF text fallback failed (pdfplumber/pdfminer/PyPDF2). Hydration then relies on TEI only. Try a different PDF or a different extraction backend.
+
+- `incorrect startxref pointer` or similar PDF syntax warnings:
+  The PDF appears malformed. Often recoverable, but if hydration fails, obtain a clean copy.
+
+- Summary lines:
+  - `Missing TEI for N papers`: GROBID output missing for those PDFs.
+  - `Missing definition spans` / `Missing context spans`: nothing matched after TEI + hash + anchor + PDF fallback.
+  - `Hydrated from PDF fallback`: spans were reconstructed from PDF text (not TEI).
+
 ## Legal CSV schema (marker columns)
+
 - `definition_char_start`, `definition_char_end`: exact TEI substring span (optional).
 - `definition_match`: `exact`/`hash`/`missing` indicating how the TEI span was found.
 - `definition_hash64`, `definition_sha256`, `definition_token_count`: full span hash.
@@ -72,18 +123,7 @@ python scripts/hydrate_defextra.py \
 - `definition_end_punct`, `context_end_punct`:
   trailing punctuation marker captured from the manual copy.
 
-## Comparing to the original (optional)
-If you maintain a private reference file with excerpts, you can compare:
-```
-python scripts/compare_defextra_csvs.py \
-  --postprocess \
-  --legal data/defextra_legal.csv \
-  --ref defextra_reference.csv \
-  --hyd defextra_hydrated.csv \
-  --report defextra_diff_report.txt \
-  --report-limit 0
-```
+## Notes
 
-Notes
 - Small mismatches are expected due to PDF/GROBID text normalization.
 - Missing exact TEI spans do **not** block hydration; hash/anchor markers are used as fallback.

docs/get_pdfs.md

@@ -1,8 +1,13 @@
 # Getting PDFs for DefExtra
 
+## Overview
+
 You must supply PDFs yourself. The dataset does **not** ship any copyrighted excerpts.
 
+See [`README.md`](../README.md) for the high‑level overview and examples.
+
 ## Recommended sources
+
 - **Semantic Scholar**: most `paper_id` values are Semantic Scholar IDs. You can open
   `https://www.semanticscholar.org/paper/<paper_id>` and download the PDF when available.
 - **DOI landing pages**: use `https://doi.org/<paper_doi>` to locate the publisher PDF.
@@ -11,19 +16,23 @@ You must supply PDFs yourself. The dataset does **not** ship any copyrighted exc
   `https://aclanthology.org/2024.lrec-main.952`.
 
 ## Helper script
-Generate a CSV of required PDFs and links:
-```
-python scripts/list_defextra_pdfs.py \
+
+Generate a CSV of required PDFs and links (pre-generated [in the repo](../defextra_required_pdfs.csv)):
+
+```bash
+uv run python scripts/list_defextra_pdfs.py \
   --legal-csv data/defextra_legal.csv \
   --output-csv defextra_required_pdfs.csv \
   --output-md defextra_required_pdfs.md
 ```
 
 The output includes:
+
 - `preferred_pdf_name` (the filename we recommend you use)
 - `alias_pdf_names` (acceptable filename aliases)
 - `url_semanticscholar`, `url_doi`, `url_arxiv`, `url_acl`
 
 ## File naming
+
 Place PDFs in one folder and name them as `<paper_id>.pdf` when possible.
 DOI/arXiv/PII aliases are supported (see `alias_pdf_names` in the helper output).

pyproject.toml

@@ -0,0 +1,16 @@
+[project]
+name = "defextra-dataset"
+version = "0.1.0"
+description = "DefExtra hydration utilities (legal release)"
+requires-python = ">=3.10"
+dependencies = [
+  "grobid-client-python>=0.0.9",
+  "lxml>=4.9",
+  "pdfplumber>=0.10",
+  "pdfminer.six>=20221105",
+  "PyPDF2>=3.0",
+  "pyarrow>=14.0",
+]
+
+[tool.uv]
+package = false

scripts/defextra_markers.py

@@ -151,27 +151,33 @@ def extract_text_from_pdf(path: Path) -> str:
         pdfplumber_module = None
     pdfplumber_any: Any = pdfplumber_module
     if pdfplumber_any is not None:
-        texts = []
-        with pdfplumber_any.open(str(path)) as pdf:
-            for page in pdf.pages:
-                page_text = page.extract_text() or ""
-                words_text = ""
-                try:
-                    words = page.extract_words(
-                        use_text_flow=True,
-                        keep_blank_chars=False,
-                    )
-                    if words:
-                        words_text = " ".join(w.get("text", "") for w in words)
-                except Exception:
+        try:
+            texts = []
+            with pdfplumber_any.open(str(path)) as pdf:
+                for page in pdf.pages:
+                    page_text = page.extract_text() or ""
                     words_text = ""
-                if words_text and words_text not in page_text:
-                    if page_text:
-                        page_text = f"{page_text}\n{words_text}"
-                    else:
-                        page_text = words_text
-                texts.append(page_text)
-        return "\n\n".join(texts)
+                    try:
+                        words = page.extract_words(
+                            use_text_flow=True,
+                            keep_blank_chars=False,
+                        )
+                        if words:
+                            words_text = " ".join(
+                                w.get("text", "") for w in words
+                            )
+                    except Exception:
+                        words_text = ""
+                    if words_text and words_text not in page_text:
+                        if page_text:
+                            page_text = f"{page_text}\n{words_text}"
+                        else:
+                            page_text = words_text
+                    texts.append(page_text)
+            return "\n\n".join(texts)
+        except Exception:
+            # pdfplumber can choke on some PDFs; fall back below.
+            pass
     try:
         from pdfminer.high_level import extract_text
     except Exception:  # pragma: no cover - optional dependency

scripts/hydrate_defextra.py

@@ -932,22 +932,22 @@ def main() -> None:
                     pdf_hash_mismatches.append(
                         {"paper_id": paper_id, "pdf": str(pdf_path)},
                     )
-                if not args.allow_pdf_hash_mismatch:
-                    if pdf_direct_match:
+                    if not args.allow_pdf_hash_mismatch and pdf_direct_match:
                         print(
                             f"Warning: PDF hash markers did not match for {pdf_path.name}; "
                             "skipping PDF (use --allow-pdf-hash-mismatch to override).",
                             file=sys.stderr,
                         )
+                    elif args.allow_pdf_hash_mismatch:
+                        print(
+                            f"Warning: PDF hash markers did not match for {pdf_path.name}; "
+                            "continuing with direct filename match.",
+                            file=sys.stderr,
+                        )
+                if not args.allow_pdf_hash_mismatch:
                     pdf_path = None
                     pdf_token_index = None
                     pdf_direct_match = False
-                else:
-                    print(
-                        f"Warning: PDF hash markers did not match for {pdf_path.name}; "
-                        "continuing with direct filename match.",
-                        file=sys.stderr,
-                    )
         if pdf_path is None and hash_specs:
             pdf_paths = list({p for p in pdf_index.values()})
             if pdf_paths: