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<item>
  <id>05980414</id>
  <dt>a</dt>
  <an>05980414</an>
  <augroup>
    <au>Kalyanpur, Aditya</au>
    <au>Murdock, J.William</au>
    <au>Fan, James</au>
    <au>Welty, Christopher</au>
  </augroup>
  <ti>Leveraging community-built knowledge for type coercion in question answering.</ti>
  <so>Aroyo, Lora (ed.) et al., The semantic web -- ISWC 2011. 10th international semantic web conference, Bonn, Germany, October 23--27, 2011. Proceedings, Part II. Berlin: Springer (ISBN 978-3-642-25092-7/pbk). Lecture Notes in Computer Science 7032, 144-156 (2011).</so>
  <py>2011</py>
  <pu>Berlin: Springer</pu>
  <lagroup>
    <la>EN</la>
  </lagroup>
  <ccgroup>
  </ccgroup>
  <utgroup>
    <ut>question answering</ut>
    <ut>type checking</ut>
    <ut>ontologies</ut>
    <ut>linked data</ut>
  </utgroup>
  <cigroup>
  </cigroup>
  <ligroup>
    <li>doi:10.1007/978-3-642-25093-4_10</li>
  </ligroup>
  <abgroup>
    <ab>Summary: Watson, the winner of the Jeopardy! challenge, is a state-of-the-art open-domain Question Answering system that tackles the fundamental issue of answer typing by using a novel type coercion (TyCor) framework, where candidate answers are initially produced without considering type information, and subsequent stages check whether the candidate can be coerced into the expected answer type. In this paper, we provide a high-level overview of the TyCor framework and discuss how it is integrated in Watson, focusing on and evaluating three TyCor components that leverage the community-built semi-structured and structured knowledge resources -- DBpedia (in conjunction with the YAGO ontology), Wikipedia Categories and Lists. These resources complement each other well in terms of precision and granularity of type information, and through links to Wikipedia, provide coverage for a large set of instances.</ab>
    <rv></rv>
  </abgroup>
</item>