Přehled o publikaci
2025
Prompting Large Language Models for Church Slavic Translation
SIGNORONI, Edoardo and Pavel RYCHLÝBasic information
Original name
Prompting Large Language Models for Church Slavic Translation
Authors
SIGNORONI, Edoardo and Pavel RYCHLÝ
Edition
Brno, Proceedings of the Nineteenth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2025, p. 57-68, 12 pp. 2025
Publisher
Tribun EU
Other information
Language
English
Type of outcome
Proceedings paper
Country of publisher
Czech Republic
Confidentiality degree
is not subject to a state or trade secret
Publication form
electronic version available online
References:
Marked to be transferred to RIV
No
Organization
Fakulta informatiky – Repository – Repository
ISBN
978-80-263-1858-3
ISSN
Keywords in English
Large Language Models; Machine Translation; Church Slavic; Low-Resource Languages; Historical Languages
Links
LM2023062, research and development project.
Changed: 9/1/2026 00:51, RNDr. Daniel Jakubík
Abstract
In the original language
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.