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0891-2017
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1530-9312
2014 Impact factor:
1.23

Computational Linguistics

Paola Merlo, Editor
March 2013, Vol. 39, No. 1, Pages 87-119
(doi: 10.1162/COLI_a_00136)
© 2013 Association for Computational Linguistics
Data-Driven Parsing using Probabilistic Linear Context-Free Rewriting Systems
Article PDF (286.71 KB)
Abstract

This paper presents the first efficient implementation of a weighted deductive CYK parser for Probabilistic Linear Context-Free Rewriting Systems (PLCFRSs). LCFRS, an extension of CFG, can describe discontinuities in a straightforward way and is therefore a natural candidate to be used for data-driven parsing. To speed up parsing, we use different context-summary estimates of parse items, some of them allowing for A* parsing. We evaluate our parser with grammars extracted from the German NeGra treebank. Our experiments show that data-driven LCFRS parsing is feasible and yields output of competitive quality.