测试ChatGPT生成词典条目的效率与智能水平
Der Effizienz- und Intelligenzbegriff in der Lexikographie und kuenstlichen Intelligenz: kann ChatGPT die lexikographische Textsorte nachbilden?
- 用德语-加利西亚语对照实验，分析ChatGPT生成词典条目的表现
- 对比其输出与真实词典数据，发现生成结果有结构但缺乏深度
- 适合语言学、AI与词典学交叉研究者参考
通过德语与加利西亚语的试点实验，本文探讨了词典学与人工智能中的效率与智能概念。研究旨在基于实证与统计方法，分析ChatGPT 3.5在生成词典条目（lexicographical text type）方面的表现，以及该聊天机器人所依赖的词典数据特征。采用定量与定性相结合的方法，评估多次相同提示下ChatGPT 3.5的输出。一方面，比较智能系统在生成词典条目上的算法性能与真实词典数据；另一方面，对聊天机器人提供的文本片段进行特定词典文本类型的分析。研究结果不仅有助于评估该聊天机器人在词典条目生成上的效率，也深入揭示了词典学与人工智能中智能的本质、思维过程与操作逻辑。
原文摘要 · Abstract (English)
By means of pilot experiments for the language pair German and Galician, this paper examines the concept of efficiency and intelligence in lexicography and artificial intelligence, AI. The aim of the experiments is to gain empirically and statistically based insights into the lexicographical text type,dictionary article, in the responses of ChatGPT 3.5, as well as into the lexicographical data on which this chatbot was trained. Both quantitative and qualitative methods are used for this purpose. The analysis is based on the evaluation of the outputs of several sessions with the same prompt in ChatGPT 3.5. On the one hand, the algorithmic performance of intelligent systems is evaluated in comparison with data from lexicographical works. On the other hand, the ChatGPT data supplied is analysed using specific text passages of the aforementioned lexicographical text type. The results of this study not only help to evaluate the efficiency of this chatbot regarding the creation of dictionary articles, but also to delve deeper into the concept of intelligence, the thought processes and the actions to be carried out in both disciplines.
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