LexNLP: Natural Language Processing and Information Extraction For Legal and Regulatory Texts (Bommarito, Katz, Detterman)

Paper Abstract – LexNLP is an open source Python package focused on natural language processing and machine learning for legal and regulatory text. The package includes functionality to (i) segment documents, (ii) identify key text such as titles and section headings, (iii) extract over eighteen types of structured information like distances and dates, (iv) extract named entities such as companies and geopolitical entities, (v) transform text into features for model training, and (vi) build unsupervised and supervised models such as word embedding or tagging models. LexNLP includes pre-trained models based on thousands of unit tests drawn from real documents available from the SEC EDGAR database as well as various judicial and regulatory proceedings. LexNLP is designed for use in both academic research and industrial applications, and is distributed at https://github.com/LexPredict/lexpredict-lexnlp

Bar-Ilan University Workshop on Law & Big Data

Academic Tour Continues – tomorrow I will be giving a talk at Bar Ilan University here in Tel Aviv at their Law & Big Data Workshop – it is looks like an good agenda with proper scientific papers with technical results / or discussions about methodology.  #LegalScience   #LegalData   #LegalInformatics

Vilnius LegalTech 2018 – Professor Katz to Deliver Keynote Address in Vilnius, Lithuania

Tomorrow – it is my great pleasure to deliver the Keynote Address at one the first #LegalTech events in Lithuania. The event will be opened by the Mayor of Vilnius – Remigijus Šimašius and Lyra Jakulevičienė (Dean of the Mykolas Romeris University Law School).  LegalTech is a global phenomenon!

Blockchain, Crypto Infrastructure and the Transaction Cost View of Economic History

Blockchain, Crypto Infrastructure and the Transaction Cost View of Economic History — This is a course module available on    BlockchainLawClass.com (check back for more over the coming weeks)