Learning Textual Entailment from Examples

author: Fabio Massimo Zanzotto, University of Milano - Bicocca
published: Feb. 25, 2007,   recorded: April 2006,   views: 4401
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Description

In this paper we present a novel approach for learning entailment relations from positive and negative examples. We define a similarity between two text-hypothesis pairs based on a syntatic and lexical information. We experimented our model within the RTE 2006 challenge obtaining the accuracy of 63.88and 62.50% for the two submissions.

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