Finding and Generating a Missing Part for Story Completion

Yusuke Mori, Hiroaki Yamane, Yusuke Mukuta, Tatsuya Harada


Abstract
Creating a story is difficult. Professional writers often experience a writer’s block. Thus, providing automatic support to writers is crucial but also challenging. Recently, in the field of generating and understanding stories, story completion (SC) has been proposed as a method for generating missing parts of an incomplete story. Despite this method’s usefulness in providing creative support, its applicability is currently limited because it requires the user to have prior knowledge of the missing part of a story. Writers do not always know which part of their writing is flawed. To overcome this problem, we propose a novel approach called “missing position prediction (MPP).” Given an incomplete story, we aim to predict the position of the missing part. We also propose a novel method for MPP and SC. We first conduct an experiment focusing on MPP, and our analysis shows that highly accurate predictions can be obtained when the missing part of a story is the beginning or the end. This suggests that if a story has a specific beginning or end, they play significant roles. We conduct an experiment on SC using MPP, and our proposed method demonstrates promising results.
Anthology ID:
2020.latechclfl-1.19
Volume:
Proceedings of the The 4th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature
Month:
December
Year:
2020
Address:
Online
Venues:
CLFL | COLING | LaTeCH | LaTeCHCLfL
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
156–166
Language:
URL:
https://aclanthology.org/2020.latechclfl-1.19
DOI:
Bibkey:
Cite (ACL):
Yusuke Mori, Hiroaki Yamane, Yusuke Mukuta, and Tatsuya Harada. 2020. Finding and Generating a Missing Part for Story Completion. In Proceedings of the The 4th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, pages 156–166, Online. International Committee on Computational Linguistics.
Cite (Informal):
Finding and Generating a Missing Part for Story Completion (Mori et al., LaTeCHCLfL 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.latechclfl-1.19.pdf
Code
 mil-tokyo/missing-position-prediction
Data
ROCStories