Full machine translation for factoid question answering

  • Authors:
  • Cristina España-Bonet;Pere R. Comas

  • Affiliations:
  • TALP Research Center, Universitat Politècnica de Catalunya (UPC);TALP Research Center, Universitat Politècnica de Catalunya (UPC)

  • Venue:
  • EACL 2012 Proceedings of the Joint Workshop on Exploiting Synergies between Information Retrieval and Machine Translation (ESIRMT) and Hybrid Approaches to Machine Translation (HyTra)
  • Year:
  • 2012

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Abstract

In this paper we present an SMT-based approach to Question Answering (QA). QA is the task of extracting exact answers in response to natural language questions. In our approach, the answer is a translation of the question obtained with an SMT system. We use the n-best translations of a given question to find similar sentences in the document collection that contain the real answer. Although it is not the first time that SMT inspires a QA system, it is the first approach that uses a full Machine Translation system for generating answers. Our approach is validated with the datasets of the TREC QA evaluation.