Prompting Large Language Models for Church Slavic Translation

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F25%3A00143188" target="_blank" >RIV/00216224:14330/25:00143188 - isvavai.cz</a>
Result on the web
<a href="https://nlp.fi.muni.cz/raslan/2025/paper3.pdf" target="_blank" >https://nlp.fi.muni.cz/raslan/2025/paper3.pdf</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Prompting Large Language Models for Church Slavic Translation
Original language description
Church Slavic is a low-resource historical language with limited resources and few experts. We explore the capabilities of off-the-shelf Large Language Models (LLMs) as Church Slavic translators by prompting multiple models in zero-shot and few-shot scenarios. We evaluate four LLMs of varying sizes on 262 sentence pairs translating Church Slavic into English and German, and conduct a second experiment examining the impact of model size using five Qwen2.5-Instruct variants. Our results show that on average EuroLLM-9B-Instruct achieves the best performance, outperforming much larger models. We find minimal benefit from few-shot prompting and performance gaps between English and German as target languages. The automated evaluation metrics suggest that LLMs can produce useful draft translations for Church Slavic, potentially assisting scholars in accessing historical texts.
Czech name
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Czech description
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Project
<a href="/en/project/LM2023062" target="_blank" >LM2023062: Digital Research Infrastructure for Language Technologies, Arts and Humanities</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the Nineteenth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2025
ISBN
9788026318583
ISSN
2336-4289
e-ISSN
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Number of pages
12
Pages from-to
57-68
Publisher name
Tribun EU
Place of publication
Brno
Event location
Kouty nad Desnou, Czech Republic
Event date
Dec 5, 2025
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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