Recognizing textual entailment using sentence similarity based on dependency tree skeletons

  • Authors:
  • Rui Wang;Günter Neumann

  • Affiliations:
  • LT-lab, DFKI, Saarbrücken, Germany;LT-lab, DFKI, Saarbrücken, Germany

  • Venue:
  • RTE '07 Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing
  • Year:
  • 2007

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Abstract

We present a novel approach to RTE that exploits a structure-oriented sentence representation followed by a similarity function. The structural features are automatically acquired from tree skeletons that are extracted and generalized from dependency trees. Our method makes use of a limited size of training data without any external knowledge bases (e.g. WordNet) or handcrafted inference rules. We have achieved an accuracy of 71.1% on the RTE-3 development set performing a 10-fold cross validation and 66.9% on the RTE-3 test data.