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Computer Science > Computation and Language

arXiv:2204.09438 (cs)
[Submitted on 20 Apr 2022]

Title:A Corpus for Understanding and Generating Moral Stories

Authors:Jian Guan, Ziqi Liu, Minlie Huang
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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.
Comments: Accepted by NAACL 2022 main conference (Long paper)
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:2204.09438 [cs.CL]
  (or arXiv:2204.09438v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2204.09438

Submission history

From: Jian Guan [view email]
[v1] Wed, 20 Apr 2022 13:12:36 UTC (3,162 KB)
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