@inproceedings{lai-li-2026-role,
title = "The Role of Prompt Language and Translation-Theory-Driven Prompts in Large Language Models: A Case Study on {S}panish{--}{C}hinese Journalistic Translation",
author = "Lai, Haohong and
Li, Weijia",
editor = "Shterionov, Dimitar and
Vanmassenhove, Eva and
De Sisto, Mirella and
Blain, Fred and
Pourmostafa Roshan Sharami, Javad and
Lepp, Lisa and
Manna, Chiara and
Rescigno, Argentina Anna and
Karakanta, Alina and
Rigouts Terryn, Ayla and
Lardelli, Manuel and
Resende, Natalia and
Murgolo, Elena and
Hackenbuchner, Jani{\c{c}}a and
Zaretskaya, Anna and
Espl{\`a}-Gomis, Miquel and
Etchegoyhen, Thierry and
Gromann, Dagmar and
Bawden, Rachel and
Haddow, Barry and
Szoc, Sara and
Forcada, Mikel and
Moniz, Helena",
booktitle = "Proceedings of the 26th Annual Conference of the {E}uropean Association for Machine Translation (Volume 1)",
month = jun,
year = "2026",
address = "Tilburg, The Netherlands",
publisher = "European Association for Machine Translation",
url = "https://aclanthology.org/2026.eamt-1.57/",
pages = "883--901",
ISBN = "9789403901411",
abstract = "This study examines the influence of prompt language and translation theory-driven prompt design on the quality of Spanish{--}Chinese editorial translations generated by GPT-5.2. A parallel corpus of four EL PA{\'I}S editorials was translated under 48 experimental conditions (4 prompt types {\texttimes} 3 prompt languages {\texttimes} 4 articles). Translation quality was assessed using BLEU and BERTScore-F1 for automated evaluation, alongside human evaluation based on the Multidimensional Quality Metrics (MQM) framework. Automated metrics identified the baseline prompt (BASE) as the best-performing condition, whereas human evaluation ranked the brief-oriented prompt (BRIEF) highest (MQM: 8.66 vs. 7.84), a reversal attributed to the single-reference constraint inherent in automated measures. Subtype analysis indicated that translation theory-driven prompts selectively reduced Awkward style errors, whereas Unidiomatic style errors persisted consistently across conditions. Prompt language exhibited negligible impact under both evaluation paradigms. These results indicate that translation theory-driven prompts are advantageous for language learners seeking high-quality editorial translations and underscore the necessity of human evaluation for accurately assessing LLM translation quality in this domain."
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<abstract>This study examines the influence of prompt language and translation theory-driven prompt design on the quality of Spanish–Chinese editorial translations generated by GPT-5.2. A parallel corpus of four EL PAÍS editorials was translated under 48 experimental conditions (4 prompt types × 3 prompt languages × 4 articles). Translation quality was assessed using BLEU and BERTScore-F1 for automated evaluation, alongside human evaluation based on the Multidimensional Quality Metrics (MQM) framework. Automated metrics identified the baseline prompt (BASE) as the best-performing condition, whereas human evaluation ranked the brief-oriented prompt (BRIEF) highest (MQM: 8.66 vs. 7.84), a reversal attributed to the single-reference constraint inherent in automated measures. Subtype analysis indicated that translation theory-driven prompts selectively reduced Awkward style errors, whereas Unidiomatic style errors persisted consistently across conditions. Prompt language exhibited negligible impact under both evaluation paradigms. These results indicate that translation theory-driven prompts are advantageous for language learners seeking high-quality editorial translations and underscore the necessity of human evaluation for accurately assessing LLM translation quality in this domain.</abstract>
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%0 Conference Proceedings
%T The Role of Prompt Language and Translation-Theory-Driven Prompts in Large Language Models: A Case Study on Spanish–Chinese Journalistic Translation
%A Lai, Haohong
%A Li, Weijia
%Y Shterionov, Dimitar
%Y Vanmassenhove, Eva
%Y De Sisto, Mirella
%Y Blain, Fred
%Y Pourmostafa Roshan Sharami, Javad
%Y Lepp, Lisa
%Y Manna, Chiara
%Y Rescigno, Argentina Anna
%Y Karakanta, Alina
%Y Rigouts Terryn, Ayla
%Y Lardelli, Manuel
%Y Resende, Natalia
%Y Murgolo, Elena
%Y Hackenbuchner, Janiça
%Y Zaretskaya, Anna
%Y Esplà-Gomis, Miquel
%Y Etchegoyhen, Thierry
%Y Gromann, Dagmar
%Y Bawden, Rachel
%Y Haddow, Barry
%Y Szoc, Sara
%Y Forcada, Mikel
%Y Moniz, Helena
%S Proceedings of the 26th Annual Conference of the European Association for Machine Translation (Volume 1)
%D 2026
%8 June
%I European Association for Machine Translation
%C Tilburg, The Netherlands
%@ 9789403901411
%F lai-li-2026-role
%X This study examines the influence of prompt language and translation theory-driven prompt design on the quality of Spanish–Chinese editorial translations generated by GPT-5.2. A parallel corpus of four EL PAÍS editorials was translated under 48 experimental conditions (4 prompt types × 3 prompt languages × 4 articles). Translation quality was assessed using BLEU and BERTScore-F1 for automated evaluation, alongside human evaluation based on the Multidimensional Quality Metrics (MQM) framework. Automated metrics identified the baseline prompt (BASE) as the best-performing condition, whereas human evaluation ranked the brief-oriented prompt (BRIEF) highest (MQM: 8.66 vs. 7.84), a reversal attributed to the single-reference constraint inherent in automated measures. Subtype analysis indicated that translation theory-driven prompts selectively reduced Awkward style errors, whereas Unidiomatic style errors persisted consistently across conditions. Prompt language exhibited negligible impact under both evaluation paradigms. These results indicate that translation theory-driven prompts are advantageous for language learners seeking high-quality editorial translations and underscore the necessity of human evaluation for accurately assessing LLM translation quality in this domain.
%U https://aclanthology.org/2026.eamt-1.57/
%P 883-901
Markdown (Informal)
[The Role of Prompt Language and Translation-Theory-Driven Prompts in Large Language Models: A Case Study on Spanish–Chinese Journalistic Translation](https://aclanthology.org/2026.eamt-1.57/) (Lai & Li, EAMT 2026)
ACL