Genetic Algorithms and Manufacturing Systems Design
Genetic Algorithms and Manufacturing Systems Design
Probabilistic DFA Inference using Kullback-Leibler Divergence and Minimality
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
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
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
On the parameter space of generative lexicalized statistical parsing models
On the parameter space of generative lexicalized statistical parsing models
Shallow parsing as part-of-speech tagging
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
Distributional phrase structure induction
ConLL '01 Proceedings of the 2001 workshop on Computational Natural Language Learning - Volume 7
Alternative approaches for generating bodies of grammar rules
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Probabilistic CFG with latent annotations
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Data-defined kernels for parse reranking derived from probabilistic models
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
Probabilistic context-free grammar induction based on structural zeros
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
A new general grammar formalism for parsing
MICAI'11 Proceedings of the 10th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
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We introduce a technique for inducing a refinement of the set of part of speech tags related to verbs. We cluster verbs according to their syntactic behavior in a dependency structure setting. The set of clusters is automatically determined by means of a quality measure over the probabilistic automata that describe words in a bilexical grammar. Each of the resulting clusters defines a new part of speech tag. We try out the resulting tag set in a state-of-the art phrase structure parser and we show that the induced part of speech tags significantly improve the accuracy of the parser.