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NAACL
2010

Syntactic/Semantic Structures for Textual Entailment Recognition

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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.
Yashar Mehdad, Alessandro Moschitti, Fabio Massimo
Added 14 Feb 2011
Updated 14 Feb 2011
Type Journal
Year 2010
Where NAACL
Authors Yashar Mehdad, Alessandro Moschitti, Fabio Massimo Zanzotto
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