“Let Your Characters Tell Their Story”: A Dataset for Character-Centric Narrative Understanding

Faeze Brahman, Meng Huang, Oyvind Tafjord, Chao Zhao, Mrinmaya Sachan, Snigdha Chaturvedi

Abstract
When reading a literary piece, readers often make inferences about various characters’ roles, personalities, relationships, intents, actions, etc. While humans can readily draw upon their past experiences to build such a character-centric view of the narrative, understanding characters in narratives can be a challenging task for machines. To encourage research in this field of character-centric narrative understanding, we present LiSCU – a new dataset of literary pieces and their summaries paired with descriptions of characters that appear in them. We also introduce two new tasks on LiSCU: Character Identification and Character Description Generation. Our experiments with several pre-trained language models adapted for these tasks demonstrate that there is a need for better models of narrative comprehension.
Anthology ID:
2021.findings-emnlp.150
Volume:
Findings of the Association for Computational Linguistics: EMNLP 2021
Month:
November
Year:
2021
Address:
Punta Cana, Dominican Republic
Venue:
Findings
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
1734–1752
Language:
URL:
https://aclanthology.org/2021.findings-emnlp.150
DOI:
10.18653/v1/2021.findings-emnlp.150
Bibkey:
Cite (ACL):
Faeze Brahman, Meng Huang, Oyvind Tafjord, Chao Zhao, Mrinmaya Sachan, and Snigdha Chaturvedi. 2021. “Let Your Characters Tell Their Story”: A Dataset for Character-Centric Narrative Understanding. In Findings of the Association for Computational Linguistics: EMNLP 2021, pages 1734–1752, Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
“Let Your Characters Tell Their Story”: A Dataset for Character-Centric Narrative Understanding (Brahman et al., Findings 2021)
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