COLING 2020main9 citations

Modeling Event Salience in Narratives via Barthes’ Cardinal Functions

Takaki Otake, Sho Yokoi, Naoya Inoue, Ryo Takahashi, Tatsuki Kuribayashi, Kentaro Inui

Abstract

Events in a narrative differ in salience: some are more important to the story than others. Estimating event salience is useful for tasks such as story generation, and as a tool for text analysis in narratology and folkloristics. To compute event salience without any annotations, we adopt Barthes’ definition of event salience and propose several unsupervised methods that require only a pre-trained language model. Evaluating the proposed methods on folktales with event salience annotation, we show that the proposed methods outperform baseline methods and find fine-tuning a language model on narrative texts is a key factor in improving the proposed methods.

BibTeX
@inproceedings{otake-etal-2020-modeling,
    title = "Modeling Event Salience in Narratives via Barthes' Cardinal Functions",
    author = "Otake, Takaki  and
      Yokoi, Sho  and
      Inoue, Naoya  and
      Takahashi, Ryo  and
      Kuribayashi, Tatsuki  and
      Inui, Kentaro",
    editor = "Scott, Donia  and
      Bel, Nuria  and
      Zong, Chengqing",
    booktitle = "Proceedings of the 28th International Conference on Computational Linguistics",
    month = dec,
    year = "2020",
    address = "Barcelona, Spain (Online)",
    publisher = "International Committee on Computational Linguistics",
    url = "https://aclanthology.org/2020.coling-main.160/",
    doi = "10.18653/v1/2020.coling-main.160",
    pages = "1784--1794"
}
Modeling Event Salience in Narratives via Barthes’ Cardinal Functions · COLING 2020