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Computer Science > Computation and Language

arXiv:2311.15509 (cs)
[Submitted on 27 Nov 2023 (v1), last revised 15 Oct 2024 (this version, v2)]

Title:A Corpus for Named Entity Recognition in Chinese Novels with Multi-genres

Authors:Hanjie Zhao, Jinge Xie, Yuchen Yan, Yuxiang Jia, Yawen Ye, Hongying Zan
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Abstract:Entities like person, location, organization are important for literary text analysis. The lack of annotated data hinders the progress of named entity recognition (NER) in literary domain. To promote the research of literary NER, we build the largest multi-genre literary NER corpus containing 263,135 entities in 105,851 sentences from 260 online Chinese novels spanning 13 different genres. Based on the corpus, we investigate characteristics of entities from different genres. We propose several baseline NER models and conduct cross-genre and cross-domain experiments. Experimental results show that genre difference significantly impact NER performance though not as much as domain difference like literary domain and news domain. Compared with NER in news domain, literary NER still needs much improvement and the Out-of-Vocabulary (OOV) problem is more challenging due to the high variety of entities in literary works. Our data and models are open-sourced at this https URL
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:2311.15509 [cs.CL]
  (or arXiv:2311.15509v2 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2311.15509

Submission history

From: Hanjie Zhao [view email]
[v1] Mon, 27 Nov 2023 03:08:41 UTC (7,880 KB)
[v2] Tue, 15 Oct 2024 12:34:26 UTC (7,880 KB)
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