Proceedings

An Inference Model for Semantic Entailment in Natural Language

Download BibTeX Cite

Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence. Pages 1678-1678.

Abstract

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. We present a principled approach to this problem that builds on inducing re-representations of text snippets into a hierarchical knowledge representation along with a sound inferential mechanism that makes use of it to prove semantic entailment.

Rodrigo de Salvo Braz, Roxana Girju, Vasin Punyakanok, Dan Roth, and Mark Sammons. 2005. An Inference Model for Semantic Entailment in Natural Language. In Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, IJCAI-05. IJCAI, 1678–1678. https://ijcai.org/proceedings/2005/350
Welcome Future Conferences AI Journal Division IJCAI Proceedings About IJCAI IJCAI Awards