Story Understanding Through Multi-Representation Model Construction

We present an implemented model of story understanding and apply it to the understanding of a children’s story. We argue that understanding a story consists of building multirepresentation models of the story and that story models are efficiently constructed using a satisfiability solver. We present a computer program that contains multiple representations of commonsense knowledge, takes a narrative as input, transforms the narrative and representations of commonsense knowledge into a satisfiability problem, runs a satisfiability solver, and produces models of the story as output. The narrative, models, and representations are expressed in the language of Shanahan’s event calculus.