An inference model for semantic entailment in natural language: Marchine Learning Challenges

Rodrigo Salvo De Braz; Corina R Girju; Vasin Punyakanok; Dan Roth; Mark Sammons

An inference model for semantic entailment in natural language: Marchine Learning Challenges

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

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

Semantic entailment is the problem of determining if the meaning of a given sentence entails that of another. We present a principled approach to semantic entailment that builds on inducing re-representations of text snippets into a hierarchical knowledge representation along with an optimization-based inferential mechanism that makes use of it to prove semantic entailment. This paper provides details and analysis of the knowledge representation and knowledge resources issues encountered. We analyze our system's behavior on the PASCAL text collection¹ and the PARC collection of question-answer pairs². This is used to motivate and explain some of the design decisions in our hierarchical knowledge representation, that is centered around a predicate-argument type abstract representation of text.

Original language	English (US)
Title of host publication	Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First PASCAL Machine Learning Challenges Workshop
Publisher	Springer
Pages	261-286
Number of pages	26
ISBN (Print)	3540334270, 9783540334279
State	Published - 2006
Event	1st PASCAL Machine Learning Challenges Workshop, MLCW 2005 - Southampton, United Kingdom Duration: Apr 11 2005 → Apr 13 2005

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3944 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	1st PASCAL Machine Learning Challenges Workshop, MLCW 2005
Country/Territory	United Kingdom
City	Southampton
Period	4/11/05 → 4/13/05

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

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De Braz, R. S., Girju, C. R., Punyakanok, V., Roth, D., & Sammons, M. (2006). An inference model for semantic entailment in natural language: Marchine Learning Challenges. In Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First PASCAL Machine Learning Challenges Workshop (pp. 261-286). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3944 LNAI). Springer.

An inference model for semantic entailment in natural language: Marchine Learning Challenges. / De Braz, Rodrigo Salvo; Girju, Corina R; Punyakanok, Vasin et al.
Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First PASCAL Machine Learning Challenges Workshop. Springer, 2006. p. 261-286 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3944 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Chapter

De Braz, RS, Girju, CR, Punyakanok, V, Roth, D & Sammons, M 2006, An inference model for semantic entailment in natural language: Marchine Learning Challenges. in Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First PASCAL Machine Learning Challenges Workshop. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3944 LNAI, Springer, pp. 261-286, 1st PASCAL Machine Learning Challenges Workshop, MLCW 2005, Southampton, United Kingdom, 4/11/05.

De Braz RS, Girju CR, Punyakanok V, Roth D, Sammons M. An inference model for semantic entailment in natural language: Marchine Learning Challenges. In Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First PASCAL Machine Learning Challenges Workshop. Springer. 2006. p. 261-286. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

De Braz, Rodrigo Salvo ; Girju, Corina R ; Punyakanok, Vasin et al. / An inference model for semantic entailment in natural language : Marchine Learning Challenges. Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First PASCAL Machine Learning Challenges Workshop. Springer, 2006. pp. 261-286 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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An inference model for semantic entailment in natural language: Marchine Learning Challenges

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