Similarity between Pairs of Co-indexed Trees for Textual Entailment Recognition

In this paper we present a novel similarity between pairs of co-indexed trees to automatically learn textual entailment classifiers. We defined a kernel function based on this similarity along with a more classical intra-pair similarity. Experiments show an improvement of 4.4 absolute percent points over state-of-the-art methods.