The syntactic process
Supertagging: an approach to almost parsing
Computational Linguistics
Investigating GIS and smoothing for maximum entropy taggers
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
Generative models for statistical parsing with Combinatory Categorial Grammar
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
A parsing: fast exact Viterbi parse selection
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Head-Driven Statistical Models for Natural Language Parsing
Computational Linguistics
Parsing the WSJ using CCG and log-linear models
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Multi-tagging for lexicalized-grammar parsing
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
The importance of supertagging for wide-coverage CCG parsing
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Iterative CKY parsing for probabilistic context-free grammars
IJCNLP'04 Proceedings of the First international joint conference on Natural Language Processing
Linear complexity context-free parsing pipelines via chart constraints
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Chart pruning for fast lexicalised-grammar parsing
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Efficient CCG parsing: A* versus adaptive supertagging
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Finite-state chart constraints for reduced complexity context-free parsing pipelines
Computational Linguistics
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The C&C CCG parser is a highly efficient linguistically motivated parser. The efficiency is achieved using a tightly-integrated supertagger, which assigns CCG lexical categories to words in a sentence. The integration allows the parser to request more categories if it cannot find a spanning analysis. We present several enhancements to the CKY chart parsing algorithm used by the parser. The first proposal is chart repair, which allows the chart to be efficiently updated by adding lexical categories individually, and we evaluate several strategies for adding these categories. The second proposal is to add constraints to the chart which require certain spans to be constituents. Finally, we propose partial beam search to further reduce the search space. Overall, the parsing speed is improved by over 35% with negligible loss of accuracy or coverage.