Learning Shallow Semantic Rules for Textual Entailment
نویسندگان
چکیده
In this paper we present a novel technique for integrating lexical-semantic knowledge in systems for learning textual entailment recognition rules: the typed anchors. These describe the semantic relations between words across an entailment pair. We integrate our approach in the cross-pair similarity model. Experimental results show that our approach increases performance of cross-pair similarity learning systems.
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Shallow Semantic in Fast Textual Entailment Rule Learners
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