LEDGAR Dataset

A LEDGAR Dataset is a labeled dataset for contract provision classification, derived from the EDGAR Database.

• Context:
  • It can be created by extracting contract provisions from documents filed with the U.S. Securities and Exchange Commission (SEC) and available on the EDGAR database.
  • It can categorize contract provisions into various legal themes or topics.
  • It can be used primarily for Natural Language Processing tasks, especially in the domain of legal technology and contract analysis.
  • It can aid in the automated understanding and classification of legal documents.
  • It can serve as a valuable resource for training and evaluating machine learning models in legal tech applications.
  • It can simplify the process of contract analysis, which traditionally requires substantial manual effort and legal expertise.
  • It can be integrated into legal tech software for purposes like contract review, risk assessment, and compliance checks.
  • ...
• Example(s):
  • LEDGAR, v202x.
  • ...
• Counter-Example(s):
  • A general-purpose language dataset not specific to legal documents.
  • Raw financial datasets from EDGAR without specific labeling for NLP tasks.
  • Datasets focused on other forms of legal documents like court opinions or legislations, rather than contracts.
• See: Contract Analysis, Natural Language Processing, Legal Technology, Machine Learning in Law, EDGAR Database, LexGLUE.

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References

2023

• (Jayakumar et al., 2023) ⇒ Thanmay Jayakumar, Fauzan Farooqui, and Luqman Farooqui. (2023). "Large Language Models Are Legal But They Are Not: Making the Case for a Powerful LegalLLM.” In: arXiv preprint arXiv:2311.08890. DOI:10.48550/arXiv.2311.08890

2020

• (Tuggener et al., 2020) ⇒ Don Tuggener, Pius Von Däniken, Thomas Peetz, and Mark Cieliebak. (2020). "LEDGAR: A Large-scale Multi-label Corpus for Text Classification of Legal Provisions in Contracts.” In: Proceedings of the Twelfth Language Resources and Evaluation Conference. [1]

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