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abstract

Natural language question answering over RDF data

Published:22 June 2013Publication History

ABSTRACT

As more and more RDF data becomes available, such as DBpedia, Yago and Freebase, it is desired to provide users with simple interfaces to access the datasets. Although the SPARQL query language is a standard way to query RDF data, it remains tedious and difficult even for expert users because of the formality of the language and the complexity of the underlying schema of RDF data. An ideal system should allow users to express queries in their own languages. In this work, we propose a methodology to translate natural language questions into SPARQL queries, which can be answered by existing RDF engines and fulfill users? information need.

References

  1. N. Nakashole, G. Weikum, and F. M. Suchanek. Patty: A taxonomy of relational patterns with semantic types. In EMNLP-CoNLL, pages 1135--1145, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. M. Yahya, K. Berberich, S. Elbassuoni, M. Ramanath, V. Tresp, and G. Weikum. Natural language questions for the web of data. In EMNLP-CoNLL, pages 379--390, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Natural language question answering over RDF data

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    • Published in

      cover image ACM Conferences
      SIGMOD '13: Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
      June 2013
      1322 pages
      ISBN:9781450320375
      DOI:10.1145/2463676

      Copyright © 2013 Copyright is held by the owner/author(s)

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 22 June 2013

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      Acceptance Rates

      SIGMOD '13 Paper Acceptance Rate76of372submissions,20%Overall Acceptance Rate785of4,003submissions,20%

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