Der Effizienz- und Intelligenzbegriff in der Lexikographie und kuenstlichen Intelligenz: kann ChatGPT die lexikographische Textsorte nachbilden?
This study addresses the problem of evaluating AI's ability to mimic specialized text creation for lexicographers and AI researchers, though it appears incremental as it applies existing methods to a new domain.
The paper investigates whether ChatGPT 3.5 can replicate lexicographical text types like dictionary articles for German and Galician, using quantitative and qualitative methods to analyze its outputs against lexicographical data, finding insights into the chatbot's efficiency and intelligence.
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.