Improving combinatory categorial grammar parse reranking with dependency grammar features

Sunghwan Mac Kim*, Dominick Ng, Mark Johnson, James R. Curran

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

1 Citation (Scopus)

Abstract

This paper presents a novel method of improving Combinatory Categorial Grammar (CCG) parsing using features generated from Dependency Grammar (DG) parses and combined using reranking. Different grammar formalisms have different strengths and different parsing models have consequently divergent views of the data. More specifically, dependency parsers are sensitive to linguistic generalisations that differ from the generalisations that the CCG parser is sensitive to, and which the reranker exploits to identify the parse most likely to be correct. We propose DG-derived reranking features, which are obtained by comparing dependencies from the CCG parser with DG dependencies, and demonstrate how they improve the performance of a CCG parser and reranker in a variety of settings. We record a final labeled F-score of 87.93% on section 23 of CCGbank, 0.5% and 0.35% improvements over the base parser (87.43%) and reranker (87.58%), respectively.

Original languageEnglish
Title of host publication24th International Conference on Computational Linguistics
Subtitle of host publicationProceedings of COLING 2012: Technical Papers
EditorsMartin Kay, Christian Boitet
Place of PublicationMumbai
PublisherIndian Institute of Technology
Pages1441-1458
Number of pages18
Publication statusPublished - 2012
Event24th International Conference on Computational Linguistics, COLING 2012 - Mumbai, India
Duration: 8 Dec 201215 Dec 2012

Other

Other24th International Conference on Computational Linguistics, COLING 2012
CountryIndia
CityMumbai
Period8/12/1215/12/12

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