Papers › Modeling Naive Psychology of Characters in Simple Commonsense Stories

Modeling Naive Psychology of Characters in Simple Commonsense Stories

16 May 2018ACL 2018 7arXiv:1805.06533archive 2025-07-28

Hannah Rashkin, Antoine Bosselut, Maarten Sap, Kevin Knight, Yejin Choi

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.

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Tasks

Emotion Classification

Datasets

Introduced by this paper, per the archive.

Story Commonsense

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Emotion Classification ROCStories NPN + Explanation Training F1 30.29 #2 of 2 Archive leaderboard report

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