• DocumentCode
    3167320
  • Title

    Computing with prepositions: Syntax

  • Author

    Stuart, Lauren M. ; Taylor, J.M. ; Raskin, Victor

  • Author_Institution
    CERIAS (Center for Educ. & Res. in Inf. Assurance & Security), Purdue Univ., West Lafayette, IN, USA
  • fYear
    2013
  • fDate
    24-28 June 2013
  • Firstpage
    929
  • Lastpage
    933
  • Abstract
    Prepositional phrase attachment has been explored as a source of both ambiguity and (not unrelated) processing errors. To date, the approaches to resolve this problem in syntactic parsing have been crisp and/or probabilistic, though some approaches look promising for the integration of fuzzy processing. Prepositions, as function words, can be described in syntactic terms, but their interactions with fuzzier content words open them up to fuzziness in use. In order to describe this fuzziness, such that we can compute with it, a set of fuzzy sets and membership functions is presented. The proposed sets and functions describe considerations in prepositional phrase attachment ambiguity, and are discussed in terms of their potential use in a computational parsing system.
  • Keywords
    computational linguistics; fuzzy set theory; grammars; computational parsing system; function word; fuzzier content word; fuzziness; fuzzy process integration; fuzzy set; membership function; prepositional phrase attachment ambiguity; syntactic parsing; syntactic term; Heating;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), 2013 Joint
  • Conference_Location
    Edmonton, AB
  • Type

    conf

  • DOI
    10.1109/IFSA-NAFIPS.2013.6608524
  • Filename
    6608524