In metalexicographical research, experts have judged the performance of technologies such as OpenAI Generative Pretrained Transformer (GPT) in lexicographic production tasks as promising yet inferior to human lexicographers. It remains unclear whether this perceived inferiority limits the effectiveness of AI-generated lexicography in resolving practical language doubts. Accordingly, this study compares the effectiveness of AI-generated definitions to those from the Macmillan English Dictionary (MED) in resolving vocabulary doubts in a multiple-choice reading task designed to test lexical knowledge. It involves 43 L2 English users in the third year of an English studies degree at a Spanish university. Students provided with MED definitions performed better on the reading task than those without access to definitions. However, there was no significant difference between the performance of students with either MED definitions or without definitions altogether, and those provided with AI-definitions. The implications of these findings are discussed along with avenues for further research.

中文翻译：

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OpenAI GPT 生成的定义与英语学习者词典中的定义在词汇导向的阅读任务中的有效性

在金属词典编纂研究中，专家们认为 OpenAI Generative Pretrained Transformer (GPT) 等技术在词典编纂任务中的表现很有前途，但不如人类词典编纂者。目前尚不清楚这种自卑感是否限制了人工智能生成的词典编纂在解决实际语言疑虑方面的有效性。因此，本研究比较了人工智能生成的定义与麦克米伦英语词典（MED）中的定义在解决旨在测试词汇知识的多项选择阅读任务中的词汇疑问方面的有效性。该项目涉及 43 名在西班牙大学攻读英语研究学位三年级的二语英语用户。获得 MED 定义的学生在阅读任务上的表现比那些没有获得定义的学生更好。然而，使用 MED 定义或完全没有定义的学生与使用 AI 定义的学生的表现没有显着差异。我们讨论了这些发现的含义以及进一步研究的途径。