Modeling Naive Psychology of Characters in Simple Commonsense Stories

2018/05/16 by Hannah Rashkin, Rashkin, Hannah, Antoine Bosselut +7 · 6 citations
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #cs.CL

paper · pdf · doi:10.48550/arxiv.1805.06533

Accepted to ACL 2018 (long paper)

arxiv created 2018/05/16 · arxiv updated 2018/05/18

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.

Cited by

• Towards High-Level Semantic Intelligence
• Social Story Frames: Contextual Reasoning about Narrative Intent and Reception
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• Growing Perspectives: Modelling Embodied Perspective Taking and Inner Narrative Development Using Large Language Models
• MotiveBench: How Far Are We From Human-Like Motivational Reasoning in Large Language Models?
• Toward Generalizable Evaluation in the LLM Era: A Survey Beyond Benchmarks

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