Korean Combinatory Categorial Grammar and Statistical Parsing.

Korean Combinatory Categorial Grammar (KCCG) is an extended combinatory categorial grammar formalism to capture the syntax and interpretation of a ``relative free'' word order, long distance scrambling, and other specific characteristics of Korean. KCCG formalism can uniformly handle word order vari...

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Publicado en:Computers & the Humanities Vol. 36; no. 4; pp. 431 - 454
Autores principales: Cha, Jeongwon, Lee, Geunbae, Lee, JongHyeok
Formato: Artículo
Publicado: Springer Nature Nov2002
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Acceso en línea:Ver este registro en EBSCOhost
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      dt: Nov2002
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          Cha, Jeongwon
          Lee, Geunbae
          Lee, JongHyeok
        affil:
          NLP Lab, Dept. of Computer Science & Engineering, Pohang University of Science and Technology (POSTECH), San 31, Hyoja-Dong, Pohang, 790-784, South Korea. E-mail:
          NLP Lab, Dept. of Computer Science & Engineering, Pohang University of Science and Technology (POSTECH), San 31, Hyoja-Dong, Pohang, 790-784, South Korea E-mail:
      su:
        Comparative grammar
        Linguistics
        Heuristic
        Methodology
        Computer programming
        Generative grammar
      sug:
        subj:
          Comparative grammar
          Linguistics
          Heuristic
          Methodology
          Computer programming
          Generative grammar
      keyword:
        CCG
        KCCG
        Korean
        Morpho-Syntactic modeling
        parsing
      ab: Korean Combinatory Categorial Grammar (KCCG) is an extended combinatory categorial grammar formalism to capture the syntax and interpretation of a ``relative free'' word order, long distance scrambling, and other specific characteristics of Korean. KCCG formalism can uniformly handle word order variations among arguments and adjuncts within a clause, as well as in complex clauses and across clause boundaries, i.e. long distance scrambling. The approach we develop takes advantage of the ability of CCG for type raising and composition along with the ability of variable categories and unordered argument modeling for relatively free word order treatment (Lee et al., 1994; Lee et al., 1997). We apply a probability model and heuristics using Korean characteristics to our KCCG parser. Results of the experiments on various text genre show that the KCCG parser performs at 87.67/87.03% constituent precision/recall.
      pubtype: Academic Journal
      doctype: Article
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    language: English
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      custom: Computers & the Humanities is a copyright of Springer, 2002. All Rights Reserved.
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