Automatic story generation systems require a body of commonsense knowledge about the basic relationships between concepts we find everyday in our world in order to produce in- teresting narratives that describe human ac- tions and world events. This paper presents an ongoing work that investigates the use of Suggested Upper Merged Ontology (SUMO) to represent storytelling knowledge and its in- ference engine Sigma to query actions and events that may take place in the story to be generated. The resulting story plan (fabula) is also represented in SUMO, allowing for a sin- gle story representation to be realized in vari- ous human languages.
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