We present KoCoNovel, an novel character coreference dataset derived from
Korean literary texts, complete with detailed annotation guidelines. Comprising
178K tokens from 50 modern and contemporary Korean novels, KoCoNovel stands as
the second-largest public coreference resolution corpus in Korean, after the
NIKL corpus, and the first to be based on literary texts. To broaden its
utility, we provide four distinct versions of KoCoNovel, offering options for
the perspectives of the omniscient author and readers, and for handling
multiple entities as either separate or overlapping. This approach integrates
existing discourse surrounding coreference resolution in literary texts,
providing a comprehensive dataset for exploration. 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 observed notable
performance enhancements with KoCoNovel in comparison to the NIKL corpus. Such
findings underscore KoCoNovel's potential to significantly enhance coreference
resolution models through the integration of Korean cultural and linguistic
dynamics.

《KoCoNovel》是一项基于韩国文学文本的创新性人物共参考数据集，从 50 部现代和当代韩国小说中提取的 178K 令牌构成，是继 NIKL 语料库之后韩国第二大公开的人物共参考解析语料库，并且是首个基于文学文本的语料库。该数据集提供四个不同版本的 KoCoNovel，为包括全知作者和读者视角以及单独或重叠处理多个实体的选项提供了选择。实验证明，使用 KoCoNovel 与 NIKL 语料库相比，基于 BERT 的人物共参考模型表现出明显的性能提升，这一发现凸显了 KoCoNovel 通过整合韩国文化和语言动态的潜力，可以显著增强人物共参考解析模型。