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Modeling Naive Psychology of Characters in Simple Commonsense Stories
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Abstract
Understanding a narrative requires reading between the lines and reasoning about the unspoken but obvious implications about events and people’s mental states — a capability that is trivial for humans but remarkably hard for machines. To facilitate research addressing this challenge, we introduce a new annotation framework to explain naive psychology of story characters as fully-specified chains of mental states with respect to motivations and emotional reactions. Our work presents a new large-scale dataset with rich low-level annotations and establishes baseline performance on several new tasks, suggesting avenues for future research.
Enabling reasoning about the cause and effect of mental state changes of characters in a story.
Browsing tool
Select one of our stories and click on individual characters to see our annotations. For dev/test stories, hover over categories to see descriptions.
Story Annotation Key
char appears in line.char doesn't appears in line.
char has a mental state change.
char doesn't have a mental state change.
Hannah Rashkin, Antoine Bosselut, Maarten Sap, Kevin Knight & Yejin Choi (2018).
Modeling Naive Psychology of Characters in Simple Commonsense Stories. ACL [view pdf]
