A maximum entropy approach to natural language processing
Computational Linguistics
SIGDOC '86 Proceedings of the 5th annual international conference on Systems documentation
Head-driven statistical models for natural language parsing
Head-driven statistical models for natural language parsing
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Question classification with support vector machines and error correcting codes
NAACL-Short '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume of the Proceedings of HLT-NAACL 2003--short papers - Volume 2
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Optimization, maxent models, and conditional estimation without magic
NAACL-Tutorials '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: Tutorials - Volume 5
Learning question classifiers: the role of semantic information
Natural Language Engineering
Incorporating non-local information into information extraction systems by Gibbs sampling
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Exploring correlation of dependency relation paths for answer extraction
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Enhanced answer type inference from questions using sequential models
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Open-domain question: answering
Foundations and Trends in Information Retrieval
Question classification using head words and their hypernyms
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
LDA based similarity modeling for question answering
SS '10 Proceedings of the NAACL HLT 2010 Workshop on Semantic Search
Question classification for email
IWCS '11 Proceedings of the Ninth International Conference on Computational Semantics
Question classification by weighted combination of lexical, syntactic and semantic features
TSD'11 Proceedings of the 14th international conference on Text, speech and dialogue
An ontology for clinical questions about the contents of patient notes
Journal of Biomedical Informatics
A support vector machine-based context-ranking model for question answering
Information Sciences: an International Journal
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In this paper, we investigate how an accurate question classifier contributes to a question answering system. We first present a Maximum Entropy (ME) based question classifier which makes use of head word features and their WordNet hypernyms. We show that our question classifier can achieve the state of the art performance in the standard UIUC question dataset. We then investigate quantitatively the contribution of this question classifier to a feature driven question answering system. With our accurate question classifier and some standard question answer features, our question answering system performs close to the state of the art using TREC corpus.