Abstract
Due to the huge scale of literary works, automatic text analysis technologies are urgently needed for literary studies such as Digital Humanities. However, the domain-generality of existing NLP technologies limits their effectiveness on in-depth literary studies. It is valuable to explore how to adapt NLP technologies to the literary-specific tasks. Fictional characters are the most essential elements of a novel, and thus crucial to understanding the content of novels. The prerequisite of collecting a character’s information is to resolve its different representations. It is a specific problem of anaphora resolution which is a classical and open-domain NLP task. We adapt a state-of-the-art anaphora resolution model to resolve character representations in Chinese novels by making some modifications, and train a widely used BERT fine-tuned model for speaker extraction as assistance. We also analyze the challenges and potential solutions for character-resolution in Chinese novels according to the resolution results on a specific Chinese novel.- Anthology ID:
- 2024.lrec-main.125
- Volume:
- Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
- Month:
- May
- Year:
- 2024
- Address:
- Torino, Italia
- Editors:
- Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
- Venues:
- LREC | COLING
- SIG:
- Publisher:
- ELRA and ICCL
- Note:
- Pages:
- 1408–1421
- Language:
- URL:
- https://aclanthology.org/2024.lrec-main.125
- DOI:
- Cite (ACL):
- Li Song and Ying Liu. 2024. Approaches and Challenges for Resolving Different Representations of Fictional Characters for Chinese Novels. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 1408–1421, Torino, Italia. ELRA and ICCL.
- Cite (Informal):
- Approaches and Challenges for Resolving Different Representations of Fictional Characters for Chinese Novels (Song & Liu, LREC-COLING 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.lrec-main.125.pdf