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To understand narrative, humans draw inferences about the underlyingrelations between narrative events. Cognitive theories of narrativeunderstanding define these inferences as four different types of causality,that include pairs of events A, B where A physically causes B (X drop, Xbreak), to pairs of events where A causes emotional state B (Y saw X, Y feltfear). Previous work on learning narrative relations from text has eitherfocused on "strict" physical causality, or has been vague about what relationis being learned. This paper learns pairs of causal events from a corpus offilm scene descriptions which are action rich and tend to be told inchronological order. We show that event pairs induced using our methods are ofhigh quality and are judged to have a stronger causal relation than event pairsfrom Rel-grams.

Inferring Narrative Causality between Event Pairs in Films