Named Entity Recognition in Context: Edit_Dunhuang team Technical Report for Evahan2025 NER Competition

Colin Brisson; Ayoub Kahfy; Marc Bui; Frédéric Constant

doi:10.18653/v1/2025.alp-1.22

Named Entity Recognition in Context: Edit_Dunhuang team Technical Report for Evahan2025 NER Competition

Colin Brisson, Ayoub Kahfy, Marc Bui, Frédéric Constant

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Abstract

We present the Named Entity Recognition sys-tem developed by the Edit Dunhuang team for the EvaHan2025 competition. Our approach in-tegrates three core components: (1) Pindola, a modern transformer-based bidirectional en-coder pretrained on a large corpus of Classi-cal Chinese texts; (2) a retrieval module that fetches relevant external context for each target sequence; and (3) a generative reasoning step that summarizes retrieved context in Classical Chinese for more robust entity disambiguation. Using this approach, we achieve an average F1 score of 85.58, improving upon the competition baseline by nearly 5 points.

Anthology ID:: 2025.alp-1.22
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:: 176–181
Language:
URL:: https://aclanthology.org/2025.alp-1.22/
DOI:: 10.18653/v1/2025.alp-1.22
Bibkey:
Cite (ACL):: Colin Brisson, Ayoub Kahfy, Marc Bui, and Frédéric Constant. 2025. Named Entity Recognition in Context: Edit_Dunhuang team Technical Report for Evahan2025 NER Competition. In Proceedings of the Second Workshop on Ancient Language Processing, pages 176–181, The Albuquerque Convention Center, Laguna. Association for Computational Linguistics.
Cite (Informal):: Named Entity Recognition in Context: Edit_Dunhuang team Technical Report for Evahan2025 NER Competition (Brisson et al., ALP 2025)
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PDF:: https://aclanthology.org/2025.alp-1.22.pdf

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@inproceedings{brisson-etal-2025-named,
    title = "Named Entity Recognition in Context: {E}dit{\_}{D}unhuang team Technical Report for Evahan2025 {NER} Competition",
    author = "Brisson, Colin  and
      Kahfy, Ayoub  and
      Bui, Marc  and
      Constant, Fr{\'e}d{\'e}ric",
    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-1.22/",
    doi = "10.18653/v1/2025.alp-1.22",
    pages = "176--181",
    ISBN = "979-8-89176-235-0",
    abstract = "We present the Named Entity Recognition sys-tem developed by the Edit Dunhuang team for the EvaHan2025 competition. Our approach in-tegrates three core components: (1) Pindola, a modern transformer-based bidirectional en-coder pretrained on a large corpus of Classi-cal Chinese texts; (2) a retrieval module that fetches relevant external context for each target sequence; and (3) a generative reasoning step that summarizes retrieved context in Classical Chinese for more robust entity disambiguation. Using this approach, we achieve an average F1 score of 85.58, improving upon the competition baseline by nearly 5 points."
}

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%0 Conference Proceedings
%T Named Entity Recognition in Context: Edit_Dunhuang team Technical Report for Evahan2025 NER Competition
%A Brisson, Colin
%A Kahfy, Ayoub
%A Bui, Marc
%A Constant, Frédéric
%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 brisson-etal-2025-named
%X We present the Named Entity Recognition sys-tem developed by the Edit Dunhuang team for the EvaHan2025 competition. Our approach in-tegrates three core components: (1) Pindola, a modern transformer-based bidirectional en-coder pretrained on a large corpus of Classi-cal Chinese texts; (2) a retrieval module that fetches relevant external context for each target sequence; and (3) a generative reasoning step that summarizes retrieved context in Classical Chinese for more robust entity disambiguation. Using this approach, we achieve an average F1 score of 85.58, improving upon the competition baseline by nearly 5 points.
%R 10.18653/v1/2025.alp-1.22
%U https://aclanthology.org/2025.alp-1.22/
%U https://doi.org/10.18653/v1/2025.alp-1.22
%P 176-181

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Markdown (Informal)

[Named Entity Recognition in Context: Edit_Dunhuang team Technical Report for Evahan2025 NER Competition](https://aclanthology.org/2025.alp-1.22/) (Brisson et al., ALP 2025)

Named Entity Recognition in Context: Edit_Dunhuang team Technical Report for Evahan2025 NER Competition (Brisson et al., ALP 2025)

ACL

Colin Brisson, Ayoub Kahfy, Marc Bui, and Frédéric Constant. 2025. Named Entity Recognition in Context: Edit_Dunhuang team Technical Report for Evahan2025 NER Competition. In Proceedings of the Second Workshop on Ancient Language Processing, pages 176–181, The Albuquerque Convention Center, Laguna. Association for Computational Linguistics.