Paper: Investigation of Question Classifier in Question Answering

ACL ID D09-1057
Title Investigation of Question Classifier in Question Answering
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2009
Authors

In this paper, we investigate how an ac- curate 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 hy- pernyms. We show that our question clas- sifier can achieve the state of the art per- formance in the standard UIUC question dataset. We then investigate quantitatively the contribution of this question classifier toafeaturedrivenquestionansweringsys- tem. With our accurate question classifier and some standard question answer fea- tures, our question answering system per- forms close to the state of the art using TREC corpus.