Understanding Restaurant Stories Using an ASP Theory of Intentions

Authors Daniela Inclezan, Qinglin Zhang, Marcello Balduccini, Ankush Israney

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Daniela Inclezan
Qinglin Zhang
Marcello Balduccini
Ankush Israney

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Daniela Inclezan, Qinglin Zhang, Marcello Balduccini, and Ankush Israney. Understanding Restaurant Stories Using an ASP Theory of Intentions. In Technical Communications of the 33rd International Conference on Logic Programming (ICLP 2017). Open Access Series in Informatics (OASIcs), Volume 58, pp. 7:1-7:4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)


The paper describes an application of logic programming to story understanding. Substantial work in this direction has been done by Erik Mueller, who focused on texts about stereotypical activities (or scripts), in particular restaurant stories. His system performed well, but could not understand 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 model scripts as activities and employ the concept of an intentional agent to reason about both normal and exceptional scenarios.
  • answer set programming
  • story understanding
  • theory of intentions


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