• DocumentCode
    3578816
  • Title

    Sentence extraction in recognition textual entailment task

  • Author

    Wibisono, Yudi ; Widyantoro, Dwi H. ; Maulidevi, Nur Ulfa

  • Author_Institution
    Sch. of Electr. Eng. & Inf., Inst. Teknol. Bandung, Bandung, Indonesia
  • fYear
    2014
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Recognizing textual entailment (RTE) is a task that predict whether a text fragment can be inferred from another text fragment. In this paper, we tackle RTE problem using sentence extraction to cover semantic variation and then extracting subject, predicate and object from each sentence without using external resources like Wordnet. Finally, similarity function is used to predict entailment relation. In sentence extraction phase, we used sentence detection, extract sentence in subordinate clause, prepositional phrase and passive sentence. Our system has accuracy of 0.63 which is comparable to other system that is not using external resources.
  • Keywords
    natural language processing; text analysis; RTE problem; entailment relation prediction; natural language processing task; object extraction; passive sentence; predicate extraction; prepositional phrase; recognition textual entailment task; semantic variation; sentence detection; sentence extraction; similarity function; subject extraction; subordinate clause; text fragment; Accuracy; Computational linguistics; Conferences; Feature extraction; Semantics; Speech; Syntactics; sentence extraction; text processing; textual entailment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data and Software Engineering (ICODSE), 2014 International Conference on
  • Print_ISBN
    978-1-4799-8175-5
  • Type

    conf

  • DOI
    10.1109/ICODSE.2014.7062670
  • Filename
    7062670