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作 者:王坤宇 成思 WANG Kunyu;CHENG Si(School of Foreign Languages,Southeast University,Nanjing 211189,China)
出 处:《浙江海洋大学学报(人文科学版)》2025年第1期86-95,共10页Journal of Zhejiang Ocean University(Humanities Sciences)
摘 要:ChatGPT的出现给自然语言处理带来变革,目前已广泛应用于各类文本生成任务,在法律翻译中亦不乏文本互译和信息检索的应用。鉴于部分法律检索平台已采用人工智能生成的立法文本译文,笔者采用BLEU、chrF++、BERTScore和COMET四种自动评估方法,同时结合ChatGPT的自我评估结果,系统评估ChatGPT在立法文本翻译和翻译质量评估中的表现。结果显示:(1)在立法文本翻译任务中,ChatGPT的表现总体低于以DeepL、百度和Google翻译为代表的神经机器翻译系统,特别是在英译中任务中存在显著差异;(2)在翻译质量评估中,ChatGPT评分与COMET评分展现出中度相关性,表明其可作为翻译质量评估的辅助工具。以上发现揭示了ChatGPT在立法文本翻译中的适用性和互补性,为法律翻译实践中的翻译系统选择及译文质量评估提供了重要的数据支持和实践参考,为新时代法治国际传播提供了新思维和新路径。ChatGPT,which has revolutionized natural language processing,has been widely used in various text generation tasks,including cross-lingual translation and information retrieval in legal translation.Given that some legal search platforms have adopted AI-generated legislative text translations,this paper systematically evaluates ChatGPT's performance in legislative text translation and translation quality assessment with four automated metrics:BLEU,chrF++,BERTScore,and COMET,along with the self-assessment results of ChatGPT.The findings show that(1) ChatGPT underperforms neural machine translation systems such as DeepL,Baidu Translate,and Google Translate in legislative text translation tasks in general,with particularly marked deficiencies in English-toChinese translations;(2) ChatGPT scores exhibit moderate correlation with COMET scores in translation quality assessment,indicating its potential as an auxiliary tool for translation quality assessment.The above findings underscore ChatGPT's applicability and complementarity in legislative text translation,furnishing empirical data and practical reference for the selection of translation systems and the assessment of translation quality in legal translation practice.Furthermore,these findings offer novel perspectives and pathways for the international dissemination of the rule of law in the new era.
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