An Inference Model for Semantic Entailment in Natural Language

Rodrigo de Salvo Braz, Roxana Girju, Vasin Punyakanok, Dan Roth, Mark Sammons

Semantic entailment is the problem of determining if the meaning of a given sentence entails that of another. This is a fundamental problem in natural language understanding that provides a broad framework for studying language variability and has a large number of applications. This paper presents a principled approach to this problem that builds on inducing representations of text snippets into a hierarchical knowledge representation along with a sound optimization-based inferential mechanism that makes use of it to decide semantic entailment. A preliminary evaluation on the PASCAL text collection is presented.

Content Area: 14. Natural Language Processing & Speech Recognition

Subjects: 13. Natural Language Processing

Submitted: May 10, 2005


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