Parsing Linear Context-Free Rewriting Systems with Fast Matrix Multiplication

Author:

Cohen Shay B.1,Gildea Daniel2

Affiliation:

1. University of Edinburgh

2. University of Rochester

Abstract

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.

Publisher

MIT Press - Journals

Subject

Artificial Intelligence,Computer Science Applications,Linguistics and Language,Language and Linguistics

Reference25 articles.

1. Indexed Grammars—An Extension of Context-Free Grammars

2. Syntax directed translations and the pushdown assembler

3. Cohen, Shay B., Giorgio Satta, and Michael Collins. 2013. Approximate PCFG parsing using tensor decomposition. In Proceedings of the 2013 Meeting of the North American chapter of the Association for Computational Linguistics (NAACL-13), pages 487–496, Atlanta, GA.

4. Products of weighted logic programs

5. Coppersmith, D. and S. Winograd. 1987. Matrix multiplication via arithmetic progressions. In Proceedings of the 19th Annual ACM Conference on Theory of Computing, pages 1–6, New York, NY.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The Composition of Dense Neural Networks and Formal Grammars for Secondary Structure Analysis;Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies;2019

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3