A Corpus for Understanding and Generating Moral Stories

Jian Guan, Ziqi Liu, Minlie Huang


Abstract
Teaching morals is one of the most important purposes of storytelling. An essential ability for understanding and writing moral stories is bridging story plots and implied morals. Its challenges mainly lie in: (1) grasping knowledge about abstract concepts in morals, (2) capturing inter-event discourse relations in stories, and (3) aligning value preferences of stories and morals concerning good or bad behavior. In this paper, we propose two understanding tasks and two generation tasks to assess these abilities of machines. We present STORAL, a new dataset of Chinese and English human-written moral stories. We show the difficulty of the proposed tasks by testing various models with automatic and manual evaluation on STORAL. Furthermore, we present a retrieval-augmented algorithm that effectively exploits related concepts or events in training sets as additional guidance to improve performance on these tasks.
Anthology ID:
2022.naacl-main.374
Volume:
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Month:
July
Year:
2022
Address:
Seattle, United States
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
5069–5087
Language:
URL:
https://aclanthology.org/2022.naacl-main.374
DOI:
10.18653/v1/2022.naacl-main.374
Bibkey:
Cite (ACL):
Jian Guan, Ziqi Liu, and Minlie Huang. 2022. A Corpus for Understanding and Generating Moral Stories. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 5069–5087, Seattle, United States. Association for Computational Linguistics.
Cite (Informal):
A Corpus for Understanding and Generating Moral Stories (Guan et al., NAACL 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.naacl-main.374.pdf
Software:
 2022.naacl-main.374.software.zip
Code
 thu-coai/moralstory
Data
ETHICSMoral Stories