Paper: Automatic Feature Engineering for Answer Selection and Extraction

ACL ID D13-1044
Title Automatic Feature Engineering for Answer Selection and Extraction
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013
Authors

This paper proposes a framework for automat- ically engineering features for two important tasks of question answering: answer sentence selection and answer extraction. We represent question and answer sentence pairs with lin- guistic structures enriched by semantic infor- mation, where the latter is produced by auto- matic classifiers, e.g., question classifier and Named Entity Recognizer. Tree kernels ap- plied to such structures enable a simple way to generate highly discriminative structural fea- tures that combine syntactic and semantic in- formation encoded in the input trees. We con- duct experiments on a public benchmark from TREC to compare with previous systems for answer sentence selection and answer extrac- tion. The results show that our models greatly improve on the state of ...