大型语言模型在非洲诗歌翻译中面向提示的文化专有项输出：一项初步的多层次表格化综述
Prompt-oriented Output of Culture-Specific Items in Translated African Poetry by Large Language Model: An Initial Multi-layered Tabular Review
- University of Antwerp（安特卫普大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文通过三个结构化提示考察ChatGPT Pro翻译非洲诗歌时文化专有项的输出，发现文化导向提示未能显著提升英译法中的文化专有项表现，并揭示了大型语言模型处理文化专有项的不一致性。
AI中文摘要：
本文考察了Chat Generative PreTrained Transformer Pro在响应三个结构化提示以翻译三部非洲诗歌选集时所生成的文化专有项输出。第一个提示较为宽泛，第二个提示聚焦于诗歌结构，第三个提示强调文化特异性。为支持该分析，本文创建了四个比较表格。第一个表格呈现了三个提示之后产生的文化专有项结果，第二个表格基于Aixela框架中的专有名词和普通表达对这些输出进行分类，第三个表格汇总了人类译者、定制翻译引擎和大型语言模型所生成的文化专有项，最后一个表格概述了Chat Generative PreTrained Transformer Pro在文化特异性提示下所采用的策略。与先前研究中参考人类译文和定制翻译引擎的文化专有项输出相比，研究结果表明，在与Chat Generative PreTrained Transformer Pro一起使用的面向文化的提示，并未在将非洲诗歌从英语翻译为法语的过程中显著提升文化专有项的表现。在五十四个文化专有项中，人类译文重复产生了三十三个文化专有项，定制翻译引擎重复产生了三十八个文化专有项，而Chat Generative PreTrained Transformer Pro重复产生了四十一个文化专有项。未被翻译的文化专有项揭示了大型语言模型在将非洲诗歌从英语翻译为法语时处理文化专有项的方法存在不一致性。
英文摘要：
This paper examines the output of cultural items generated by Chat Generative PreTrained Transformer Pro in response to three structured prompts to translate three anthologies of African poetry. The first prompt was broad, the second focused on poetic structure, and the third prompt emphasized cultural specificity. To support this analysis, four comparative tables were created. The first table presents the results of the cultural items produced after the three prompts, the second categorizes these outputs based on Aixela framework of Proper nouns and Common expressions, the third table summarizes the cultural items generated by human translators, a custom translation engine, and a Large Language Model. The final table outlines the strategies employed by Chat Generative PreTrained Transformer Pro following the culture specific prompt. Compared to the outputs of cultural items from reference human translation and the custom translation engine in prior studies the findings indicate that the culture oriented prompts used with Chat Generative PreTrained Transformer Pro did not yield significant enhancements of cultural items during the translation of African poetry from English to French. Among the fifty four cultural items, the human translation produced thirty three cultural items in repetition, the custom translation engine generated Thirty eight cultural items in repetition while Chat Generative PreTrained Transformer Pro produced forty one cultural items in repetition. The untranslated cultural items revealed inconsistencies in Large language models approach to translating cultural items in African poetry from English to French.
