LexNLP

What is LexNLP?

LexNLP is the leading open-source information retrieval and extraction tool for real, unstructured legal text.  LexNLP can be used by developers to solve problems involving contracts, plans, policies, procedures, and other material.

Who is LexNLP for?

LexNLP is for parties who want to build their own solutions or extract custom data for legal or financial documents, including corporate legal departments, law firms, CFOs, publicly-traded or registered companies, insurance companies, and accountants and auditors.  

What can LexNLP do?

LexNLP is full of functionality for natural language processing, machine learning, and information extraction, including:

  • Segmentation and tokenization, such as:
    • A sentence parser that is aware of common legal abbreviations like LLC. or F.3d.
    • Pre-trained segmentation models for legal concepts such as pages, titles, and sections
  • Pre-trained word embedding and topic models, broadly and for specific practice areas
  • Pre-trained classifiers for document type and clause type
  • Broad range of fact extraction, such as:
    • Monetary amounts, non-monetary amounts, percentages, ratios
    • Addresses, persons, companies, telephone numbers, and email addresses
    • Conditional statements and constraints, like “less than” or “later than”
    • Dates, recurring dates, and durations
    • Courts, regulations, and citations
  • Tools for building new clustering and classification methods
  • Hundreds of unit tests from real legal documents

Learn about more LexNLP features here.

What problems can LexNLP solve?

LexNLP can help organizations extract information and build custom document analytics across a wide range of problems, including contract harmonizationdiligence and M&A, high-volume and high-impact contract review,  supply chain and vendor managementand real estate and lease abstraction.

How can you use LexNLP?

LexNLP is available to organizations through a range of options, including open source AGPL licensing and commercial licensing models.  Learn more about getting started with LexNLP here.