Modeling Naive Psychology of Characters in Simple Commonsense Stories

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Contact one of the authors: Hannah, Antoine and/or Maarten.


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.


Theories of Motivation (Maslow and Reiss) and Emotional Reaction (Plutchik).

Read our paper for more:
Hannah Rashkin, Antoine Bosselut, Maarten Sap, Kevin Knight & Yejin Choi (2018).
Modeling Naive Psychology of Characters in Simple Commonsense Stories. ACL [view pdf]