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  • 标题:Parsing Linear Context-Free Rewriting Systems with Fast Matrix Multiplication
  • 本地全文:下载
  • 作者:Shay B. Cohen ; Daniel Gildea
  • 期刊名称:Computational Linguistics
  • 印刷版ISSN:0891-2017
  • 电子版ISSN:1530-9312
  • 出版年度:2016
  • 卷号:42
  • 期号:3
  • 页码:421-455
  • DOI:10.1162/COLI_a_00254
  • 语种:English
  • 出版社:MIT Press
  • 摘要:We describe a recognition algorithm for a subset of binary linear context-free rewriting systems (LCFRS) with running time O ( n ωd ) where M ( m ) = O ( m ω ) is the running time for m × m matrix multiplication and d is the “contact rank” of the LCFRS—the maximal number of combination and non-combination points that appear in the grammar rules. We also show that this algorithm can be used as a subroutine to obtain a recognition algorithm for general binary LCFRS with running time O ( n ωd +1). The currently best known ω is smaller than 2.38. Our result provides another proof for the best known result for parsing mildly context-sensitive formalisms such as combinatory categorial grammars, head grammars, linear indexed grammars, and tree-adjoining grammars, which can be parsed in time O ( n 4.76). It also shows that inversion transduction grammars can be parsed in time O ( n 5.76). In addition, binary LCFRS subsumes many other formalisms and types of grammars, for some of which we also improve the asymptotic complexity of parsing.
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