{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/lexnlp-natural-language-processing-and","title":"LexNLP: Natural language processing and information extraction for legal and regulatory texts","arxiv_id":"1806.03688","date":"2018-06-10","proceeding":null,"authors":["Michael J Bommarito II","Daniel Martin Katz","Eric M Detterman"],"abstract":"LexNLP is an open source Python package focused on natural language\nprocessing and machine learning for legal and regulatory text. The package\nincludes functionality to (i) segment documents, (ii) identify key text such as\ntitles and section headings, (iii) extract over eighteen types of structured\ninformation like distances and dates, (iv) extract named entities such as\ncompanies and geopolitical entities, (v) transform text into features for model\ntraining, and (vi) build unsupervised and supervised models such as word\nembedding or tagging models. LexNLP includes pre-trained models based on\nthousands of unit tests drawn from real documents available from the SEC EDGAR\ndatabase as well as various judicial and regulatory proceedings. LexNLP is\ndesigned for use in both academic research and industrial applications, and is\ndistributed at https://github.com/LexPredict/lexpredict-lexnlp.","url_abs":"http://arxiv.org/abs/1806.03688v1","url_pdf":"http://arxiv.org/pdf/1806.03688v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"lexnlp-natural-language-processing-and","repo_url":"https://github.com/LexPredict/lexpredict-lexnlp","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1806.03688","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}