Source-language entailment modeling for translating unknown terms

  • Authors:
  • Shachar Mirkin;Lucia Specia;Nicola Cancedda;Ido Dagan;Marc Dymetman;Idan Szpektor

  • Affiliations:
  • Bar-Ilan University;Xerox Research Centre Europe;Xerox Research Centre Europe;Bar-Ilan University;Xerox Research Centre Europe;Bar-Ilan University

  • Venue:
  • ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
  • Year:
  • 2009

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Abstract

This paper addresses the task of handling unknown terms in SMT. We propose using source-language monolingual models and resources to paraphrase the source text prior to translation. We further present a conceptual extension to prior work by allowing translations of entailed texts rather than paraphrases only. A method for performing this process efficiently is presented and applied to some 2500 sentences with unknown terms. Our experiments show that the proposed approach substantially increases the number of properly translated texts.