Make Good Use of GujiRoBERTa to Identify Entities in Ancient Chinese

Lihan Lin; Yiming Wang; Jiachen Li; Huan Ouyang; Si Li

doi:10.18653/v1/2025.alp-1.23

Make Good Use of GujiRoBERTa to Identify Entities in Ancient Chinese

Lihan Lin, Yiming Wang, Jiachen Li, Huan Ouyang, Si Li

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Abstract

This report describes our model submitted for the EvaHan 2025 shared task on named entity recognition for ancient Chinese literary works. Since we participated in the task of closed modality, our method is based on the appointed pretrained language model GujiRoBERTajian-fan and we used appointed datasets.We carried out experiments on decodingstrategies and schedulers to verify the effect of our method. In the final test, our method outperformed the official baseline, demonstrating its effectiveness. In the end, for the results, this report gives an analysis from the perspective of data composition.

Anthology ID:: 2025.alp-1.23
Volume:: Proceedings of the Second Workshop on Ancient Language Processing
Month:: May
Year:: 2025
Address:: The Albuquerque Convention Center, Laguna
Editors:: Adam Anderson, Shai Gordin, Bin Li, Yudong Liu, Marco C. Passarotti, Rachele Sprugnoli
Venues:: ALP | WS
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 182–186
Language:
URL:: https://aclanthology.org/2025.alp-1.23/
DOI:: 10.18653/v1/2025.alp-1.23
Bibkey:
Cite (ACL):: Lihan Lin, Yiming Wang, Jiachen Li, Huan Ouyang, and Si Li. 2025. Make Good Use of GujiRoBERTa to Identify Entities in Ancient Chinese. In Proceedings of the Second Workshop on Ancient Language Processing, pages 182–186, The Albuquerque Convention Center, Laguna. Association for Computational Linguistics.
Cite (Informal):: Make Good Use of GujiRoBERTa to Identify Entities in Ancient Chinese (Lin et al., ALP 2025)
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PDF:: https://aclanthology.org/2025.alp-1.23.pdf

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@inproceedings{lin-etal-2025-make,
    title = "Make Good Use of {G}uji{R}o{BERT}a to Identify Entities in {A}ncient {C}hinese",
    author = "Lin, Lihan  and
      Wang, Yiming  and
      Li, Jiachen  and
      Ouyang, Huan  and
      Li, Si",
    editor = "Anderson, Adam  and
      Gordin, Shai  and
      Li, Bin  and
      Liu, Yudong  and
      Passarotti, Marco C.  and
      Sprugnoli, Rachele",
    booktitle = "Proceedings of the Second Workshop on Ancient Language Processing",
    month = may,
    year = "2025",
    address = "The Albuquerque Convention Center, Laguna",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.alp-1.23/",
    doi = "10.18653/v1/2025.alp-1.23",
    pages = "182--186",
    ISBN = "979-8-89176-235-0",
    abstract = "This report describes our model submitted for the EvaHan 2025 shared task on named entity recognition for ancient Chinese literary works. Since we participated in the task of closed modality, our method is based on the appointed pretrained language model GujiRoBERTajian-fan and we used appointed datasets.We carried out experiments on decodingstrategies and schedulers to verify the effect of our method. In the final test, our method outperformed the official baseline, demonstrating its effectiveness. In the end, for the results, this report gives an analysis from the perspective of data composition."
}

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%0 Conference Proceedings
%T Make Good Use of GujiRoBERTa to Identify Entities in Ancient Chinese
%A Lin, Lihan
%A Wang, Yiming
%A Li, Jiachen
%A Ouyang, Huan
%A Li, Si
%Y Anderson, Adam
%Y Gordin, Shai
%Y Li, Bin
%Y Liu, Yudong
%Y Passarotti, Marco C.
%Y Sprugnoli, Rachele
%S Proceedings of the Second Workshop on Ancient Language Processing
%D 2025
%8 May
%I Association for Computational Linguistics
%C The Albuquerque Convention Center, Laguna
%@ 979-8-89176-235-0
%F lin-etal-2025-make
%X This report describes our model submitted for the EvaHan 2025 shared task on named entity recognition for ancient Chinese literary works. Since we participated in the task of closed modality, our method is based on the appointed pretrained language model GujiRoBERTajian-fan and we used appointed datasets.We carried out experiments on decodingstrategies and schedulers to verify the effect of our method. In the final test, our method outperformed the official baseline, demonstrating its effectiveness. In the end, for the results, this report gives an analysis from the perspective of data composition.
%R 10.18653/v1/2025.alp-1.23
%U https://aclanthology.org/2025.alp-1.23/
%U https://doi.org/10.18653/v1/2025.alp-1.23
%P 182-186

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Markdown (Informal)

[Make Good Use of GujiRoBERTa to Identify Entities in Ancient Chinese](https://aclanthology.org/2025.alp-1.23/) (Lin et al., ALP 2025)

Make Good Use of GujiRoBERTa to Identify Entities in Ancient Chinese (Lin et al., ALP 2025)

ACL

Lihan Lin, Yiming Wang, Jiachen Li, Huan Ouyang, and Si Li. 2025. Make Good Use of GujiRoBERTa to Identify Entities in Ancient Chinese. In Proceedings of the Second Workshop on Ancient Language Processing, pages 182–186, The Albuquerque Convention Center, Laguna. Association for Computational Linguistics.