An ASP Methodology for Understanding Narratives about Stereotypical Activities. Issue 3 (10th August 2018)

• Record Type: Journal Article
• Authors: INCLEZAN, DANIELA; ZHANG, QINGLIN; BALDUCCINI, MARCELLO; ISRANEY, ANKUSH
• Editors: Dal Palu, Alessandro; Tarau, Paul
• Is Part Of: Theory and practice of logic programming. Volume 18:Issue 3/4(2018)
• Page Start: 535
• Page End: 552
• Publication Date: 2018-08-10
• Subjects: natural language understanding, -- stereotypical activities, -- intentions; Logic programming -- Periodicals; Artificial intelligence -- Computer programs -- Periodicals; Constraint programming (Computer science) -- Periodicals; 005.115
• DOI: 10.1017/S1471068418000121
• Languages: English
• ISSNs: 1471-0684

Abstract

Abstract: We describe an application of Answer Set Programming to the understanding of narratives about stereotypical activities, demonstrated via question answering. Substantial work in this direction was done by Erik Mueller, who modeled stereotypical activities as scripts . His systems were able to understand a good number of narratives, but could not process texts describing exceptional scenarios. We propose addressing this problem by using a theory of intentions developed by Blount, Gelfond, and Balduccini. We present a methodology in which we substitute scripts by activities (i.e., hierarchical plans associated with goals) and employ the concept of an intentional agent to reason about both normal and exceptional scenarios. We exemplify the application of this methodology by answering questions about a number of restaurant stories. This paper is under consideration for acceptance in TPLP.