An inference model for semantic entailment in natural language

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

Research output: Contribution to journalConference article

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.

Original languageEnglish (US)
Pages (from-to)1678-1679
Number of pages2
JournalIJCAI International Joint Conference on Artificial Intelligence
StatePublished - Dec 1 2005
Event19th International Joint Conference on Artificial Intelligence, IJCAI 2005 - Edinburgh, United Kingdom
Duration: Jul 30 2005Aug 5 2005

Fingerprint

Semantics
Knowledge representation
Acoustic waves

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

An inference model for semantic entailment in natural language. / De Salvo Braz, Rodrigo; Girju, Roxana; Punyakanok, Vasin; Roth, Dan; Sammons, Mark.

In: IJCAI International Joint Conference on Artificial Intelligence, 01.12.2005, p. 1678-1679.

Research output: Contribution to journalConference article

De Salvo Braz, Rodrigo ; Girju, Roxana ; Punyakanok, Vasin ; Roth, Dan ; Sammons, Mark. / An inference model for semantic entailment in natural language. In: IJCAI International Joint Conference on Artificial Intelligence. 2005 ; pp. 1678-1679.
@article{c083895325f54d0d98de894808a3c84b,
title = "An inference model for semantic entailment in natural language",
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.",
author = "{De Salvo Braz}, Rodrigo and Roxana Girju and Vasin Punyakanok and Dan Roth and Mark Sammons",
year = "2005",
month = "12",
day = "1",
language = "English (US)",
pages = "1678--1679",
journal = "IJCAI International Joint Conference on Artificial Intelligence",
issn = "1045-0823",

}

TY - JOUR

T1 - An inference model for semantic entailment in natural language

AU - De Salvo Braz, Rodrigo

AU - Girju, Roxana

AU - Punyakanok, Vasin

AU - Roth, Dan

AU - Sammons, Mark

PY - 2005/12/1

Y1 - 2005/12/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84880731808&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84880731808&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:84880731808

SP - 1678

EP - 1679

JO - IJCAI International Joint Conference on Artificial Intelligence

JF - IJCAI International Joint Conference on Artificial Intelligence

SN - 1045-0823

ER -