Accurate methods for the statistics of surprise and coincidence
Computational Linguistics - Special issue on using large corpora: I
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
PCFG models of linguistic tree representations
Computational Linguistics
A maximum-entropy-inspired parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
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
Efficient parsing for bilexical context-free grammars and head automaton grammars
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Automatic compensation for parser figure-of-merit flaws
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on 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
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Coarse-to-fine n-best parsing and MaxEnt discriminative reranking
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Comparing and combining finite-state and context-free parsers
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Parsing '05 Proceedings of the Ninth International Workshop on Parsing Technology
Searching for Part of Speech Tags That Improve Parsing Models
GoTAL '08 Proceedings of the 6th international conference on Advances in Natural Language Processing
Sparse multi-scale grammars for discriminative latent variable parsing
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Fast and accurate arc filtering for dependency parsing
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
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We present a method for induction of concise and accurate probabilistic context-free grammars for efficient use in early stages of a multi-stage parsing technique. The method is based on the use of statistical tests to determine if a non-terminal combination is unobserved due to sparse data or hard syntactic constraints. Experimental results show that, using this method, high accuracies can be achieved with a non-terminal set that is orders of magnitude smaller than in typically induced probabilistic context-free grammars, leading to substantial speed-ups in parsing. The approach is further used in combination with an existing reranker to provide competitive WSJ parsing results.