• DocumentCode
    3026327
  • Title

    A modified approach for extraction and association of triplets

  • Author

    Jaiswal, Anuja ; George, Vinai

  • Author_Institution
    Dept. of Inf. Technol., Christ Univ., Bangalore, India
  • fYear
    2015
  • fDate
    15-16 May 2015
  • Firstpage
    36
  • Lastpage
    40
  • Abstract
    In this paper we present an enhanced algorithm with modified approach to extricate various Triplets i.e. subject-predicate-object from Natural language sentences. The Treebank Structure and the Typed Dependencies obtained from Stanford Parser are used to elicit multiple triplets from English Sentences. Typed Dependencies represents grammatical connections among the words of any sentence and represents how triplets are associated. The intended interpretation behind the extraction of Triplets is that the subject is acting on the object in a way described by the predicate. In graphical form it can be considered that subject and object will be acting as nodes i.e. entities and predicate as edges i.e. relationship. The resulting triplets and relations can be useful for building and analysis of a social network graph and for generating communication pattern and Information retrieval.
  • Keywords
    grammars; graph theory; information retrieval; natural language processing; social networking (online); text analysis; English sentences; Stanford parser; communication pattern generation; grammatical connections; information retrieval; natural language sentences; social network graph analysis; subject-predicate-object; treebank structure; triplet association; triplet extraction; triplet extrication; typed dependencies; Artificial neural networks; Automation; Conferences; Natural languages; Pragmatics; Random access memory; Syntactics; extraction; information retrieval; parsing; relationship; triplets;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing, Communication & Automation (ICCCA), 2015 International Conference on
  • Conference_Location
    Noida
  • Print_ISBN
    978-1-4799-8889-1
  • Type

    conf

  • DOI
    10.1109/CCAA.2015.7148367
  • Filename
    7148367