Procedure for quantitatively comparing the syntactic coverage of English grammars
HLT '91 Proceedings of the workshop on Speech and Natural Language
Discriminative Reranking for Natural Language Parsing
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
A maximum-entropy-inspired parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
A dependency-based method for evaluating broad-coverage parsers
Natural Language Engineering
Three generative, lexicalised models for statistical parsing
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Inducing history representations for broad coverage statistical parsing
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Intricacies of Collins' Parsing Model
Computational Linguistics
Head-Driven Statistical Models for Natural Language Parsing
Computational Linguistics
Discriminative training of a neural network statistical parser
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
Learning accurate, compact, and interpretable tree annotation
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Effective self-training for parsing
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of 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
The impact of parse quality on syntactically-informed statistical machine translation
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
IWPT '07 Proceedings of the 10th International Conference on Parsing Technologies
Evaluating and integrating treebank parsers on a biomedical corpus
Software '05 Proceedings of the Workshop on Software
Descriptive and empirical approaches to capturing underlying dependencies among parsing errors
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
SemEval-2010 task 12: Parser evaluation using textual entailments
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
Evaluation of dependency parsers on unbounded dependencies
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Beam-width prediction for efficient context-free parsing
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Parser evaluation over local and non-local deep dependencies in a large corpus
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Analysis of the difficulties in Chinese deep parsing
IWPT '11 Proceedings of the 12th International Conference on Parsing Technologies
Efficient matrix-encoded grammars and low latency parallelization strategies for CYK
IWPT '11 Proceedings of the 12th International Conference on Parsing Technologies
Parser evaluation using elementary dependency matching
IWPT '11 Proceedings of the 12th International Conference on Parsing Technologies
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Constituency parser performance is primarily interpreted through a single metric, F-score on WSJ section 23, that conveys no linguistic information regarding the remaining errors. We classify errors within a set of linguistically meaningful types using tree transformations that repair groups of errors together. We use this analysis to answer a range of questions about parser behaviour, including what linguistic constructions are difficult for state-of-the-art parsers, what types of errors are being resolved by rerankers, and what types are introduced when parsing out-of-domain text.