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Deep answers for naturally asked questions on the web of data

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Published:16 April 2012Publication History

ABSTRACT

We present DEANNA, a framework for natural language question answering over structured knowledge bases. Given a natural language question, DEANNA translates questions into a structured SPARQL query that can be evaluated over knowledge bases such as Yago, Dbpedia, Freebase, or other Linked Data sources. DEANNA analyzes questions and maps verbal phrases to relations and noun phrases to either individual entities or semantic classes. Importantly, it judiciously generates variables for target entities or classes to express joins between multiple triple patterns. We leverage the semantic type system for entities and use constraints in jointly mapping the constituents of the question to relations, classes, and entities. We demonstrate the capabilities and interface of DEANNA, which allows advanced users to influence the translation process and to see how the different components interact to produce the final result.

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          cover image ACM Other conferences
          WWW '12 Companion: Proceedings of the 21st International Conference on World Wide Web
          April 2012
          1250 pages
          ISBN:9781450312301
          DOI:10.1145/2187980

          Copyright © 2012 ACM

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          Publication History

          • Published: 16 April 2012

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