mlsanityData to 7 Oct 2026

KoCoNovel: Annotated Dataset of Character Coreference in Korean Novels

arXiv 2404.01140 ↗First posted 1 Apr 2024cs.CLcited by 1

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Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 10 of its 28 references that are in the map. First posted on arXiv 1 Apr 2024.

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10 of 28 references.

References · 10

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  5. 2019BERT for Coreference Resolution: Baselines and Analysiscited by 125
  6. 2021KLUE: Korean Language Understanding Evaluationcited by 113
  7. 2019An Annotated Dataset of Coreference in English Literaturecited by 57
  8. 2020Revealing the Myth of Higher-Order Inference in Coreference Resolutioncited by 49
  9. 2021Coreference Resolution without Span Representationscited by 45
  10. 2022LingMess: Linguistically Informed Multi Expert Scorers for Coreference Resolutioncited by 26

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