Syntactic/Semantic Structures for Textual Entailment Recognition

In this paper, we describe an approach based on off-the-shelf parsers and semantic resources for the Recognizing Textual Entailment (RTE) challenge that can be generally applied to any domain. Syntax is exploited by means of tree kernels whereas lexical semantics is derived from heterogeneous resources, e.g. WordNet or distributional semantics through Wikipedia. The joint syntactic/semantic model is realized by means of tree kernels, which can exploit lexical relatedness to match syntactically similar structures, i.e. whose lexical compounds are related. The comparative experiments across different RTE challenges and traditional systems show that our approach consistently and meaningfully achieves high accuracy, without requiring any adaptation or tuning.