Towards overcoming the knowledge acquisition bottleneck in answer set prolog applications: Embracing natural language inputs

Chitta Baral, Juraj Dzifcak, Luis Tari

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Answer set Prolog, or AnsProlog in short, is one of the leading knowledge representation (KR) languages with a large body of theoretical and building block results, several implementations and reasoning and declarative problem solving applications. But it shares the problem associated with knowledge acquisition with all other KR languages; most knowledge is entered manually by people and that is a bottleneck. Recent advances in natural language processing have led to some systems that convert natural language sentences to a logical form. Although these systems are in their infancy, they suggest a direction to overcome the above mentioned knowledge acquisition bottleneck. In this paper we discuss some recent work by us on developing applications that process logical forms of natural language text and use the processed result together with AnsProlog rules to do reasoning and problem solving.

Original languageEnglish (US)
Title of host publicationLogic Programming - 23rd International Conference, ICLP 2007, Proceedings
PublisherSpringer Verlag
Pages1-21
Number of pages21
ISBN (Print)9783540746089
DOIs
StatePublished - 2007
Event23rd International Conference on Logic Programming, ICLP 2007 - Porto, Portugal
Duration: Sep 8 2007Sep 13 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4670 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other23rd International Conference on Logic Programming, ICLP 2007
CountryPortugal
CityPorto
Period9/8/079/13/07

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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