  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.
