One of the most powerful and enduring ideas in written discourse analysis is that genres can be described in terms of the moves which structure a writer's purpose. Considerable research has sought to identify these distinct communicative acts, but analyses have been beset by problems of subjectivity, reliability and the time-consuming need for multiple coders to confirm analyses. In this paper we employ the affordances of GPT-4 to automate the annotation process by using natural language prompts. Focusing on abstracts from articles in four applied linguistics journals, we devise prompts which enable the model to identify moves effectively. The annotated outputs of these prompts were evaluated by two assessors with a third addressing disagreements. The results show that an 8-shot prompt was more effective than one using two, confirming that the inclusion of examples illustrating areas of variability can enhance GPT-4's ability to recognize multiple moves in a single sentence and reduce bias related to textual position. We suggest that GPT-4 offers considerable potential in automating this annotation process, when human actors with domain specific linguistic expertise inform the prompting process.

本研究探讨了如何利用GPT-4来自动化研究文章摘要写作策略的标注过程，以解决现有分析方法主观性和可靠性的问题。通过对应用语言学期刊的摘要进行分析，研究发现采用包含示例的8-shot提示比2-shot提示更加有效，表明GPT-4能够更好地识别复杂句子中的多个写作策略。这一方法显著提升了分析效率，具有广泛的自动标注潜力。 

GPT-4能否学习分析研究文章摘要中的写作策略？