Parsing the WSJ using CCG and log-linear models

Authors:
Stephen Clark;James R. Curran
Affiliations:
University of Edinburgh, Edinburgh, UK;University of Sydney, Australia
Venue:
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Year:
2004

Citing 14
Cited 81

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Abstract

This paper describes and evaluates log-linear parsing models for Combinatory Categorial Grammar (CCG). A parallel implementation of the L-BFGS optimisation algorithm is described, which runs on a Beowulf cluster allowing the complete Penn Treebank to be used for estimation. We also develop a new efficient parsing algorithm for CCG which maximises expected recall of dependencies. We compare models which use all CCG derivations, including non-standard derivations, with normal-form models. The performances of the two models are comparable and the results are competitive with existing wide-coverage CCG parsers.