In this paper we define a novel similarity
measure between examples of textual entailments and we use it as a kernel function in Support Vector Machines (SVMs).
This allows us to automatically learn the
rewrite rules that describe a non trivial set
of entailment cases. The experiments with
the data sets of the RTE 2005 challenge
show an improvement of 4.4% over the state-of-the-art methods