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Shared Heritage, Distinct Writing: Rethinking Resource Selection for East Asian Historical Documents

arXiv 2411.04822 ↗First posted 7 Nov 2024cs.CLcited by 1

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Abstract (arXiv)

Historical documents in the Sinosphere are known to share common formats and practices, particularly in veritable records compiled by court historians. This shared linguistic heritage has led researchers to use Classical Chinese resources for cross-lingual transfer when processing historical documents from Korea and Japan, which remain relatively low-resource. In this paper, we question the assumption of cross-lingual transferability from Classical Chinese to Hanja and Kanbun, the ancient written languages of Korea and Japan, respectively. Our experiments across machine translation, named entity recognition, and punctuation restoration tasks show minimal impact of Classical Chinese datasets on language model performance for ancient Korean documents written in Hanja, with performance differences within ±0.0068 F1-score for sequence labeling tasks and up to +0.84 BLEU score for translation. These limitations persist consistently across various model sizes, architectures, and domain-specific datasets. Our analysis reveals that the benefits of Classical Chinese resources diminish rapidly as local language data increases for Hanja, while showing substantial improvements only in extremely low-resource scenarios for both Korean and Japanese historical documents. These findings emphasize the need for careful empirical validation rather than assuming benefits from indiscriminate cross-lingual transfer.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 14 of its 28 references that are in the map. First posted on arXiv 7 Nov 2024.

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14 of 28 references.

References · 14

  1. 2023Efficient Memory Management for Large Language Model Serving with PagedAttentioncited by 5,767
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  8. 2023WYWEB: A NLP Evaluation Benchmark For Classical Chinesecited by 10
  9. 2021Restoring and Mining the Records of the Joseon Dynasty via Neural Language Modeling and Machine Translationcited by 9
  10. 2023SikuGPT: A Generative Pre-trained Model for Intelligent Information Processing of Ancient Texts from the Perspective of Digital Humanitiescited by 9
  11. 2023HistRED: A Historical Document-Level Relation Extraction Datasetcited by 7
  12. 2022Translating Hanja Historical Documents to Contemporary Korean and Englishcited by 6
2 more
  1. 2022HUE: Pretrained Model and Dataset for Understanding Hanja Documents of Ancient Koreacited by 5
  2. 2023Kanbun-LM: Reading and Translating Classical Chinese in Japanese Methods by Language Modelscited by 3

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