FrameNet-Based Shallow Semantic Parsing with a POS Tagger

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Author(s)

Abstract

In this paper we propose a FrameNet-based shallow semantic parsing without syntactic parsing. Previous studies on shallow semantic parsing utilize the results of syntactic parsing of input sentences as input data. However, syntactic parsing has well-known shortfalls, such as large amount of computation and insufficient accuracy etc… Further-more, when use of syntactic parsing is premised, it limits applicable languages, since good syntactic parser is rarely available. To prevent such undesirable consequences in shallow semantic parsing, we propose to use POS tagger instead of syntactic parsing. Our experiments using FrameNetll data as training and test data showed the same level performance as existing methods using syntactic parsing.

Journal

  • IEICE technical report. Artificial intelligence and knowledge-based processing

    IEICE technical report. Artificial intelligence and knowledge-based processing 104(488), 7-10, 2004-12-07

    The Institute of Electronics, Information and Communication Engineers

References:  7

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    FLEISCHMAN Michael

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    THOMPSON Cynthia A.

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    DOI  Cited by (2)

Codes

  • NII Article ID (NAID)
    110003205590
  • NII NACSIS-CAT ID (NCID)
    AN10013061
  • Text Lang
    ENG
  • Article Type
    ART
  • ISSN
    09135685
  • NDL Article ID
    7222334
  • NDL Source Classification
    ZN33(科学技術--電気工学・電気機械工業--電子工学・電気通信)
  • NDL Call No.
    Z16-940
  • Data Source
    CJP  NDL  NII-ELS 
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