Challenges in Processing Chinese Texts Across Genres and Eras

Minghao Zheng; Sarah Moeller

Challenges in Processing Chinese Texts Across Genres and Eras

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Abstract

Pre-trained Chinese Natural Language Processing (NLP) tools show reduced performance when analyzing poetry compared to prose. This study investigates the discrepancies between tools trained on either Classical or Modern Chinese prose when handling Classical Chinese prose and Classical Chinese poetry. Three experiments reveal error patterns that indicate the weaker performance on Classical Chinese poemsis due to challenges identifying word boundaries. Specifically, tools trained on Classical prose struggle recognizing word boundaries within Classical poetic structures and tools trained on Modern prose have difficulty with word segmentation in both Classical Chinese genres. These findings provide valuable insights into the limitations of current NLP tools for studying Classical Chinese literature.

Anthology ID:: 2025.winlp-main.34
Volume:: Proceedings of the 9th Widening NLP Workshop
Month:: November
Year:: 2025
Address:: Suzhou, China
Editors:: Chen Zhang, Emily Allaway, Hua Shen, Lesly Miculicich, Yinqiao Li, Meryem M'hamdi, Peerat Limkonchotiwat, Richard He Bai, Santosh T.y.s.s., Sophia Simeng Han, Surendrabikram Thapa, Wiem Ben Rim
Venues:: WiNLP | WS
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 230–234
Language:
URL:: https://aclanthology.org/2025.winlp-main.34/
DOI:
Bibkey:
Cite (ACL):: Minghao Zheng and Sarah Moeller. 2025. Challenges in Processing Chinese Texts Across Genres and Eras. In Proceedings of the 9th Widening NLP Workshop, pages 230–234, Suzhou, China. Association for Computational Linguistics.
Cite (Informal):: Challenges in Processing Chinese Texts Across Genres and Eras (Zheng & Moeller, WiNLP 2025)
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PDF:: https://aclanthology.org/2025.winlp-main.34.pdf

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@inproceedings{zheng-moeller-2025-challenges,
    title = "Challenges in Processing {C}hinese Texts Across Genres and Eras",
    author = "Zheng, Minghao  and
      Moeller, Sarah",
    editor = "Zhang, Chen  and
      Allaway, Emily  and
      Shen, Hua  and
      Miculicich, Lesly  and
      Li, Yinqiao  and
      M'hamdi, Meryem  and
      Limkonchotiwat, Peerat  and
      Bai, Richard He  and
      T.y.s.s., Santosh  and
      Han, Sophia Simeng  and
      Thapa, Surendrabikram  and
      Rim, Wiem Ben",
    booktitle = "Proceedings of the 9th Widening NLP Workshop",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.winlp-main.34/",
    pages = "230--234",
    ISBN = "979-8-89176-351-7",
    abstract = "Pre-trained Chinese Natural Language Processing (NLP) tools show reduced performance when analyzing poetry compared to prose. This study investigates the discrepancies between tools trained on either Classical or Modern Chinese prose when handling Classical Chinese prose and Classical Chinese poetry. Three experiments reveal error patterns that indicate the weaker performance on Classical Chinese poemsis due to challenges identifying word boundaries. Specifically, tools trained on Classical prose struggle recognizing word boundaries within Classical poetic structures and tools trained on Modern prose have difficulty with word segmentation in both Classical Chinese genres. These findings provide valuable insights into the limitations of current NLP tools for studying Classical Chinese literature."
}

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%0 Conference Proceedings
%T Challenges in Processing Chinese Texts Across Genres and Eras
%A Zheng, Minghao
%A Moeller, Sarah
%Y Zhang, Chen
%Y Allaway, Emily
%Y Shen, Hua
%Y Miculicich, Lesly
%Y Li, Yinqiao
%Y M’hamdi, Meryem
%Y Limkonchotiwat, Peerat
%Y Bai, Richard He
%Y T.y.s.s., Santosh
%Y Han, Sophia Simeng
%Y Thapa, Surendrabikram
%Y Rim, Wiem Ben
%S Proceedings of the 9th Widening NLP Workshop
%D 2025
%8 November
%I Association for Computational Linguistics
%C Suzhou, China
%@ 979-8-89176-351-7
%F zheng-moeller-2025-challenges
%X Pre-trained Chinese Natural Language Processing (NLP) tools show reduced performance when analyzing poetry compared to prose. This study investigates the discrepancies between tools trained on either Classical or Modern Chinese prose when handling Classical Chinese prose and Classical Chinese poetry. Three experiments reveal error patterns that indicate the weaker performance on Classical Chinese poemsis due to challenges identifying word boundaries. Specifically, tools trained on Classical prose struggle recognizing word boundaries within Classical poetic structures and tools trained on Modern prose have difficulty with word segmentation in both Classical Chinese genres. These findings provide valuable insights into the limitations of current NLP tools for studying Classical Chinese literature.
%U https://aclanthology.org/2025.winlp-main.34/
%P 230-234

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Markdown (Informal)

[Challenges in Processing Chinese Texts Across Genres and Eras](https://aclanthology.org/2025.winlp-main.34/) (Zheng & Moeller, WiNLP 2025)

Challenges in Processing Chinese Texts Across Genres and Eras (Zheng & Moeller, WiNLP 2025)

ACL

Minghao Zheng and Sarah Moeller. 2025. Challenges in Processing Chinese Texts Across Genres and Eras. In Proceedings of the 9th Widening NLP Workshop, pages 230–234, Suzhou, China. Association for Computational Linguistics.