• DocumentCode
    3228625
  • Title

    A Natural Language Processing and Semantic-Based System for Contract Analysis

  • Author

    Dan Yang ; Leber, C. ; Tari, Luis ; Chandramouli, Aravind ; Crapo, Andrew ; Messmer, Richard ; Gustafson, Steven

  • Author_Institution
    GE Global Res., Niskayuna, NY, USA
  • fYear
    2013
  • fDate
    4-6 Nov. 2013
  • Firstpage
    707
  • Lastpage
    712
  • Abstract
    The Contract Search Tool is a semantic search platform that enables effective analysis of complex, long-term contractual service agreement for machines such as gas turbines. The approach we developed can effectively identify paragraphs of text for specific legal concepts. Then the key content can be decomposed and organized by the semantics model that captures key elements of the concepts and links to specific paragraphs. This is achieved by performing semantic text analysis to capture implicitly-stated provisions and the definitions of provisions, and relevant information is returned in an organized manner. The tool can be applied to increase productivity of legal review, share legal knowledge with service managers, and reduce legal risk in contract review process.
  • Keywords
    artificial intelligence; contracts; gas turbines; natural language processing; service industries; text analysis; contract analysis; contract review process; contract search tool; contractual service agreement; gas turbines; implicitly-stated provisions; legal concepts; legal knowledge sharing; legal review; legal risk reduction; natural language processing; semantic text analysis; semantic-based system; semantics model; text paragraphs identification; Artificial intelligence; Contracts; Data mining; Law; Semantics; Syntactics; Natural language processing; contract analysis; information extraction; information retrieval; semantics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence (ICTAI), 2013 IEEE 25th International Conference on
  • Conference_Location
    Herndon, VA
  • ISSN
    1082-3409
  • Print_ISBN
    978-1-4799-2971-9
  • Type

    conf

  • DOI
    10.1109/ICTAI.2013.109
  • Filename
    6735320