Parsing Linear Context-Free Rewriting Systems with Fast Matrix Multiplication
Author(s) -
Shay B. Cohen,
Daniel Gildea
Publication year - 2016
Publication title -
computational linguistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.314
H-Index - 98
eISSN - 1530-9312
pISSN - 0891-2017
DOI - 10.1162/coli_a_00254
Subject(s) - computer science , parsing , rotation formalisms in three dimensions , indexed grammar , rewriting , time complexity , tree adjoining grammar , l attributed grammar , rule based machine translation , binary tree , phrase structure grammar , context sensitive grammar , context free grammar , algorithm , theoretical computer science , programming language , artificial intelligence , mathematics , geometry
We describe a recognition algorithm for a subset of binary linear context-free rewriting systems (LCFRS) with running time O(nωd) where M(m) = O(mω) 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(nωd+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(n4.76). It also shows that inversion transduction grammars can be parsed in time O(n5.76). 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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