An Application of ASP Theories of Intentions to Understanding Restaurant Scenarios: Insights and Narrative Corpus

Zhang, Qinglin, Benton, Chris, Inclezan, Daniela

arXiv.org Artificial Intelligence 

This paper presents a practical application of Answer Set Programming to the understanding of narratives about restaurants. While this task was investigated in depth by Erik Mueller, exceptional scenarios remained a serious challenge for his script-based story comprehension system. We present a methodology that remedies this issue by modeling characters in a restaurant episode as intentional agents. We focus especially on the refinement of certain components of this methodology in order to increase coverage and performance. We present a restaurant story corpus that we created to design and evaluate our methodology.

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