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Human engagement in narrative is partially driven by reasoning about discourse relations between narrative events, and the expectations about what is likely to happen next that results from such reasoning. Researchers in NLP have tackled modeling such expectations from a range of perspectives, including treating it as the inference of the CONTINGENT(More)
The increased use of large corpora in narrative research has created new opportunities for empirical research and intelligent narrative technologies. To best exploit the value of these corpora, several research groups are eschewing complex discourse analysis techniques in favor of high-level minimalist narrative annotation schemes that can be quickly(More)
This paper describes work on automatically identifying categories of narrative clauses in personal stories written by ordinary people about their daily lives and experiences. We base our approach on Labov & Walet-zky's theory of oral narrative which categorizes narrative clauses into subtypes, such as ORIENTATION, ACTION and EVALUATION. We describe an(More)
Interactive storytelling encompasses a wide variety of applications and systems that aim to allow players in a virtual world to affect the narrative progression prescribed by the author. The story world is often modeled by a set of hand-crafted causal and temporal relationships that define the possible narrative sequences based on the user's actions. In our(More)
Much of the user-generated content on social media is provided by ordinary people telling stories about their daily lives. We develop and test a novel method for learning fine-grained common-sense knowledge from these stories about contingent (causal and conditional) relationships between everyday events. This type of knowledge is useful for text and story(More)
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