Legal Natural Language Processing (NLP) Benchmark Task

A Legal Natural Language Processing (NLP) Benchmark Task is an domain-specific NLP benchmark task for a legal text analysis task.

• Context:
  • It can (often) be essential for Legal NLP Model Training that require understanding complex legal jargon and terminology.
  • It can include tasks like legal document summarization, legal information extraction, and legal question answering.
  • It can include datasets derived from legal documents, court rulings, or legal literature.
  • It can play a critical role in advancing the field of legal tech and AI in law.
  • ...
• Example(s):
  • LEXTREME: A comprehensive multi-lingual and multi-task benchmark for the legal domain.
  • LegalBench.
  • ContractNLI.
  • ...
• Counter-Example(s):
  • Clinical Trial Dataset,
  • ImageNet Dataset,
  • Question-Answer Dataset,
  • Reading Comprehension Dataset.
  • General Language Understanding Evaluation (GLUE): A benchmark designed for general language understanding.
  • Stanford Question Answering Dataset (SQuAD): A benchmark for general question answering tasks.
  • TREC Legal Track: A track within TREC focusing on e-discovery rather than a broad range of legal NLP tasks.
• See: Biomedical NLP Benchmark, General NLP Benchmark, Natural Language Understanding

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References

2023

• (Greco & Tagarelli, 2023) ⇒ Candida M Greco, and Andrea Tagarelli. (2023). “Bringing Order Into the Realm of Transformer-based Language Models for Artificial Intelligence and Law.” In: Artif. Intell. Law Journal. doi:10.48550/arXiv.2308.05502

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