ACORD: An Expert-Annotated Retrieval Dataset for Legal Contract Drafting
ACL 2025, 24739–24762
What it adds
Graded relevance judgments for drafting-oriented clause retrieval.
Read with this limitation
Many one-star negatives inherit relevance from other clause categories; describing every pair as individually expert-rated would overstate the annotation process.
- Jurisdiction tags
- United States
- Language
- English
Follow the source
Selected statements located in the linked primary sources. These results have not been independently reproduced here.
The benchmark has 114 queries and more than 126,000 query-clause pairs.
3 and Table 2, printed 24743–24744BM25 plus GPT-4o reranking reports NDCG@10 79.7 versus 54.0 for BM25 alone.
5, printed 24745
Connected research
Same research topic · no citation implied
CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review
Same research topic · no citation implied
ContractNLI: A Dataset for Document-level Natural Language Inference for Contracts
Entry status, source edition & rights
- Index entry
- Source-linked summary, prepared with agent assistance. Independent scholarly review is pending.
- Archive admission
- This bibliographic entry does not confer admission to the versioned archive.
- Edition inspected
- 10.18653/v1/2025.acl-long.1206
- Reading coverage
- Published sections 2–7, Table 3, Appendices A–C and selected implementation details; project/repository documentation.
- Rights
- External references only. Papers and research artifacts remain with their original hosts; their own terms apply.
- Entry updated
- 2026-10-15
Source-linked summary · independent assessment pending.