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Fast Statistical Parsing with Parallel Multiple Context-Free Grammars

Conference paper
Authors Krasimir Angelov
Peter Ljunglöf
Published in EACL'14, 14th Conference of the European Chapter of the Association for Computational Linguistics
Publication year 2014
Published at Department of Computer Science and Engineering, Computing Science (GU)
Language en
Links www.aclweb.org/anthology/E14-1039
https://gup.ub.gu.se/file/139042
Subject categories Language Technology (Computational Linguistics)

Abstract

We present an algorithm for incremental statistical parsing with Parallel Multiple Context-Free Grammars (PMCFG). This is an extension of the algorithm by Angelov (2009) to which we added statistical ranking. We show that the new algorithm is several times faster than other statistical PMCFG parsing algorithms on real-sized grammars. At the same time the algorithm is more general since it supports non-binarized and non-linear grammars. We also show that if we make the search heuristics non-admissible, the parsing speed improves even further, at the risk of returning sub-optimal solutions.

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