Exploiting Wikipedia and EuroWordNet to solve Cross-Lingual Question Answering

  • Authors:

  • Sergio Ferrández;Antonio Toral;íscar Ferrández;Antonio Ferrández;Rafael Muñoz

  • Affiliations:

  • Natural Language Processing and Information Systems Group, Department of Computing Languages and Systems, University of Alicante, P.O. Box 99, E-03080 Alicante, Spain;Istituto di Linguistica Computazionale, Consiglio Nazionale delle Ricerche, Pisa, Italy;Natural Language Processing and Information Systems Group, Department of Computing Languages and Systems, University of Alicante, P.O. Box 99, E-03080 Alicante, Spain;Natural Language Processing and Information Systems Group, Department of Computing Languages and Systems, University of Alicante, P.O. Box 99, E-03080 Alicante, Spain;Natural Language Processing and Information Systems Group, Department of Computing Languages and Systems, University of Alicante, P.O. Box 99, E-03080 Alicante, Spain

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2009

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Abstract

This paper describes a new advance in solving Cross-Lingual Question Answering (CL-QA) tasks. It is built on three main pillars: (i) the use of several multilingual knowledge resources to reference words between languages (the Inter Lingual Index (ILI) module of EuroWordNet and the multilingual knowledge encoded in Wikipedia); (ii) the consideration of more than only one translation per word in order to search candidate answers; and (iii) the analysis of the question in the original language without any translation process. This novel approach overcomes the errors caused by the common use of Machine Translation (MT) services by CL-QA systems. We also expose some studies and experiments that justify the importance of analyzing whether a Named Entity should be translated or not. Experimental results in bilingual scenarios show that our approach performs better than an MT based CL-QA approach achieving an average improvement of 36.7%.