Discourse complements lexical semantics for non-factoid answer reranking

Research output: Chapter in Book/Report/Conference proceedingConference contribution

56 Scopus citations

Abstract

We propose a robust answer reranking model for non-factoid questions that integrates lexical semantics with discourse information, driven by two representations of discourse: a shallow representation centered around discourse markers, and a deep one based on Rhetorical Structure Theory. We evaluate the proposed model on two corpora from different genres and domains: one from Yahoo! Answers and one from the biology domain, and two types of non-factoid questions: manner and reason. We experimentally demonstrate that the discourse structure of nonfactoid answers provides information that is complementary to lexical semantic similarity between question and answer, improving performance up to 24% (relative) over a state-of-the-art model that exploits lexical semantic similarity alone. We further demonstrate excellent domain transfer of discourse information, suggesting these discourse features have general utility to non-factoid question answering.

Original languageEnglish (US)
Title of host publicationLong Papers
PublisherAssociation for Computational Linguistics (ACL)
Pages977-986
Number of pages10
ISBN (Print)9781937284725
StatePublished - Jan 1 2014
Event52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014 - Baltimore, MD, United States
Duration: Jun 22 2014Jun 27 2014

Publication series

Name52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014 - Proceedings of the Conference
Volume1

Other

Other52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014
CountryUnited States
CityBaltimore, MD
Period6/22/146/27/14

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language

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  • Cite this

    Jansen, P., Surdeanu, M., & Clark, P. (2014). Discourse complements lexical semantics for non-factoid answer reranking. In Long Papers (pp. 977-986). (52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014 - Proceedings of the Conference; Vol. 1). Association for Computational Linguistics (ACL).