Using Referring Expression Generation to Model Literary Style

Nick Montfort, Ardalan SadeghiKivi, Joanne Yuan, Alan Y. Zhu


Abstract
Novels and short stories are not just remarkable because of what events they represent. The narrative style they employ is significant. To understand the specific contributions of different aspects of this style, it is possible to create limited symbolic models of narrating that hold almost all of the narrative discourse constant while varying a single aspect. In this paper we use a new implementation of a system for narrative discourse generation, Curveship, to change how existents at the story level are named. This by itself allows for the telling of the same underlying story in ways that evoke, for instance, a fabular or parable-like mode, the style of narrator Patrick Bateman in Brett Easton Ellis’s American Psycho, and the unusual dialect of Anthony Burgess’s A Clockwork Orange.
Anthology ID:
2021.nlp4dh-1.8
Volume:
Proceedings of the Workshop on Natural Language Processing for Digital Humanities
Month:
December
Year:
2021
Address:
NIT Silchar, India
Editors:
Mika Hämäläinen, Khalid Alnajjar, Niko Partanen, Jack Rueter
Venue:
NLP4DH
SIG:
Publisher:
NLP Association of India (NLPAI)
Note:
Pages:
64–74
Language:
URL:
https://aclanthology.org/2021.nlp4dh-1.8
DOI:
Bibkey:
Cite (ACL):
Nick Montfort, Ardalan SadeghiKivi, Joanne Yuan, and Alan Y. Zhu. 2021. Using Referring Expression Generation to Model Literary Style. In Proceedings of the Workshop on Natural Language Processing for Digital Humanities, pages 64–74, NIT Silchar, India. NLP Association of India (NLPAI).
Cite (Informal):
Using Referring Expression Generation to Model Literary Style (Montfort et al., NLP4DH 2021)
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PDF:
https://aclanthology.org/2021.nlp4dh-1.8.pdf
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