KoCoNovel: Annotated Dataset of Character Coreference in Korean Novels

Fuente: arXiv
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Auteurs principaux: Kim, Kyuhee, Lee, Surin, Lee, Sangah
Format: Preprint
Publié: 2024
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author Kim, Kyuhee
Lee, Surin
Lee, Sangah
author_facet Kim, Kyuhee
Lee, Surin
Lee, Sangah
contents In this paper, we present KoCoNovel, a novel character coreference dataset derived from Korean literary texts, complete with detailed annotation guidelines. Comprising 178K tokens from 50 modern and contemporary novels, KoCoNovel stands as one of the largest public coreference resolution corpora in Korean, and the first to be based on literary texts. KoCoNovel offers four distinct versions to accommodate a wide range of literary coreference analysis needs. These versions are designed to support perspectives of the omniscient author or readers, and to manage multiple entities as either separate or overlapping, thereby broadening its applicability. One of KoCoNovel's distinctive features is that 24% of all character mentions are single common nouns, lacking possessive markers or articles. This feature is particularly influenced by the nuances of Korean address term culture, which favors the use of terms denoting social relationships and kinship over personal names. In experiments with a BERT-based coreference model, we observe notable performance enhancements with KoCoNovel in character coreference tasks within literary texts, compared to a larger non-literary coreference dataset. Such findings underscore KoCoNovel's potential to significantly enhance coreference resolution models through the integration of Korean cultural and linguistic dynamics.
format Preprint
id arxiv_https___arxiv_org_abs_2404_01140
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle KoCoNovel: Annotated Dataset of Character Coreference in Korean Novels
Kim, Kyuhee
Lee, Surin
Lee, Sangah
Computation and Language
In this paper, we present KoCoNovel, a novel character coreference dataset derived from Korean literary texts, complete with detailed annotation guidelines. Comprising 178K tokens from 50 modern and contemporary novels, KoCoNovel stands as one of the largest public coreference resolution corpora in Korean, and the first to be based on literary texts. KoCoNovel offers four distinct versions to accommodate a wide range of literary coreference analysis needs. These versions are designed to support perspectives of the omniscient author or readers, and to manage multiple entities as either separate or overlapping, thereby broadening its applicability. One of KoCoNovel's distinctive features is that 24% of all character mentions are single common nouns, lacking possessive markers or articles. This feature is particularly influenced by the nuances of Korean address term culture, which favors the use of terms denoting social relationships and kinship over personal names. In experiments with a BERT-based coreference model, we observe notable performance enhancements with KoCoNovel in character coreference tasks within literary texts, compared to a larger non-literary coreference dataset. Such findings underscore KoCoNovel's potential to significantly enhance coreference resolution models through the integration of Korean cultural and linguistic dynamics.
title KoCoNovel: Annotated Dataset of Character Coreference in Korean Novels
topic Computation and Language
url https://arxiv.org/abs/2404.01140