Published online by Cambridge University Press: 22 April 2019
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.
We would like to thank Zengzhi Jiang, Keya Patel, and Marcello Balduccini for their help in retrieving excerpts from Google Books and Project Gutenberg.