Der Effizienz- und Intelligenzbegriff in der Lexikographie und kuenstlichen Intelligenz: kann ChatGPT die lexikographische Textsorte nachbilden?

TL;DR

This study empirically evaluates ChatGPT 3.5's ability to emulate lexicographical dictionary articles in German and Galician, analyzing its efficiency and intelligence in producing such specialized texts.

Contribution

It provides novel empirical insights into ChatGPT's performance in generating lexicographical texts and compares it with traditional lexicographical data and methods.

Findings

ChatGPT's outputs show partial emulation of lexicographical texts.

The chatbot's performance varies across sessions and prompts.

Insights into AI's capabilities and limitations in specialized text generation.

Abstract

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.