Learning textual entailment from examples
Fm Zanzotto, Alessandro Moschitti, Marco Pennacchiotti, Mt Pazienza · Cineca Institutional Research Information System (Tor Vergata University) · 2006
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 syntactic and lexical information.We experimented our model within the RTE 2006 challenge obtaining the accuracy of 63.88% and 62.50% for the two submissions.