Robust conversion of CCG derivations to phrase structure trees

Authors:
Jonathan K. Kummerfeld;Dan Klein;James R. Curran
Affiliations:
University of California, Berkeley, Berkeley, CA;University of California, Berkeley, Berkeley, CA;University of Sydney, Sydney, Australia
Venue:
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Short Papers - Volume 2
Year:
2012

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Abstract

We propose an improved, bottom-up method for converting CCG derivations into PTB-style phrase structure trees. In contrast with past work (Clark and Curran, 2009), which used simple transductions on category pairs, our approach uses richer transductions attached to single categories. Our conversion preserves more sentences under round-trip conversion (51.1% vs. 39.6%) and is more robust. In particular, unlike past methods, ours does not require ad-hoc rules over non-local features, and so can be easily integrated into a parser.