Modeling Naive Psychology of Characters in Simple Commonsense Stories
Hannah Rashkin, Antoine Bosselut, Maarten Sap, Kevin Knight, Yejin Choi
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.- Anthology ID:
- P18-1213
- Volume:
- Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Month:
- July
- Year:
- 2018
- Address:
- Melbourne, Australia
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2289–2299
- Language:
- URL:
- https://aclanthology.org/P18-1213
- DOI:
- 10.18653/v1/P18-1213
- Cite (ACL):
- Hannah Rashkin, Antoine Bosselut, Maarten Sap, Kevin Knight, and Yejin Choi. 2018. Modeling Naive Psychology of Characters in Simple Commonsense Stories. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 2289–2299, Melbourne, Australia. Association for Computational Linguistics.
- Cite (Informal):
- Modeling Naive Psychology of Characters in Simple Commonsense Stories (Rashkin et al., ACL 2018)
- PDF:
- https://preview.aclanthology.org/nodalida-main-page/P18-1213.pdf
- Data
- Story Commonsense, ROCStories