
摘要: 本文探讨了人工智能辅助语言学研究的多种方法,特别是提示工程(Prompt Engineering)在大语言模型中的应用。提示工程通过结构化输入和角色扮演等方法,提升了模型的准确性和效用。文章还介绍了AI代码生成、智能学术团队的构建以及大语言模型的本地化应用。通过具体案例,如《上海地方志》的标点和翻译,展示了AI在语言学研究中的潜力和应用前景。 关键词: 提示工程、大语言模型、AI代码生成、智能学术团队、本地化应用、GPT4All、LM Studio,检索增强生成(RAG)
Artificial intelligence, FOS: Languages and literature, Linguistics
Artificial intelligence, FOS: Languages and literature, Linguistics
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