A* CCG Parsing with a Supertag-factored Model

Mike Lewis, Mark Steedman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We introduce a new CCG parsing model which is factored on lexical category assignments. Parsing is then simply a deterministic search for the most probable category sequence that supports a CCG derivation. The parser is extremely simple, with a tiny feature set, no POS tagger, and no statistical model of the derivation or dependencies. Formulating the model in this way allows a highly effective heuristic for A* parsing, which makes parsing extremely fast. Compared to the standard C&C CCG parser, our model is more accurate out-of-domain, is four times faster, has higher coverage, and is greatly simplified. We also show that using our parser improves the performance of a state-of-the-art question answering system.
Original languageEnglish
Title of host publicationProceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Place of PublicationDoha, Qatar
PublisherAssociation for Computational Linguistics
Pages990-1000
Number of pages11
DOIs
Publication statusPublished - 1 Oct 2014
Event2014 Conference on Empirical Methods in Natural Language Processing - Doha, Qatar
Duration: 25 Oct 201429 Oct 2014
http://emnlp2014.org/

Conference

Conference2014 Conference on Empirical Methods in Natural Language Processing
Abbreviated titleEMNLP 2014
CountryQatar
CityDoha
Period25/10/1429/10/14
Internet address

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