Learning and Inference for Clause Identification
ECML '02 Proceedings of the 13th European 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 new statistical parser based on bigram lexical dependencies
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Chunking with support vector machines
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Fast methods for kernel-based text analysis
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Introduction to the CoNLL-2000 shared task: chunking
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
Introduction to the CoNLL-2001 shared task: clause identification
ConLL '01 Proceedings of the 2001 workshop on Computational Natural Language Learning - Volume 7
Classifying chart cells for quadratic complexity context-free inference
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
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
LCC-WSD: system description for English coarse grained all words task at SemEval 2007
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Unsupervised argument identification for Semantic Role Labeling
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Finite-state chart constraints for reduced complexity context-free parsing pipelines
Computational Linguistics
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Parsing is a computationally intensive task due to the combinatorial explosion seen in chart parsing algorithms that explore possible parse trees. In this paper, we propose a method to limit the combinatorial explosion by restricting the CYK chart parsing algorithm based on the output of a chunk parser. When tested on the three parsers presented in (Collins, 1999), we observed an approximate three-fold speedup with only an average decrease of 0.17% in both precision and recall.