The syntactic process
Discriminative Reranking for Natural Language Parsing
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Efficient normal-form parsing for combinatory categorial grammar
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Building deep dependency structures with a wide-coverage CCG parser
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Parsing with generative models of predicate-argument structure
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Learning to distinguish PP arguments from adjuncts
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Parsing the WSJ using CCG and log-linear models
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Coarse-to-fine n-best parsing and MaxEnt discriminative reranking
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Creating a CCGbank and a wide-coverage CCG lexicon for German
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
Evaluating the accuracy of an unlexicalized statistical parser on the PARC DepBank
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
CCGbank: A Corpus of CCG Derivations and Dependency Structures Extracted from the Penn Treebank
Computational Linguistics
Wide-coverage efficient statistical parsing with ccg and log-linear models
Computational Linguistics
Parsing '05 Proceedings of the Ninth International Workshop on Parsing Technology
Chinese CCGbank: extracting CCG derivations from the Penn Chinese Treebank
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Training a log-linear parser with loss functions via softmax-margin
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
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Optimising for one grammatical representation, but evaluating over a different one is a particular challenge for parsers and n-best CCG parsing. We find that this mismatch causes many n-best CCG parses to be semantically equivalent, and describe a hashing technique that eliminates this problem, improving oracle n-best F-score by 0.7% and reranking accuracy by 0.4%. We also present a comprehensive analysis of errors made by the C&C CCG parser, providing the first breakdown of the impact of implementation decisions, such as supertagging, on parsing accuracy.