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

TL;DR

This paper applies ASP theories of intentions to interpret restaurant narratives by modeling characters as intentional agents, improving coverage and performance with a new corpus and methodology.

Contribution

It introduces a novel ASP-based methodology for understanding restaurant stories by modeling characters as intentional agents, addressing previous limitations.

Findings

Created a restaurant story corpus for evaluation

Enhanced coverage and performance of narrative understanding

Demonstrated effectiveness of ASP in modeling intentions

Abstract

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. Under consideration in Theory and Practice of Logic Programming (TPLP).