A Study of Conversational Intentionalities Expressed in Natural Language Using ChatGPT
摘要
The goal of this study is two-fold: (1) to evaluate the usefulness and reliability of ChatGPT as a tool for detecting and generating nontrivial semantic categories of text, characterized by various conversational intentionalities, and (2) to build a semantic map of intentionalities and characterize its topological and geometric properties. ChatGPT 3.5 was used in this work. Results demonstrate reproducibility and reasonable accuracy. Furthermore, it was found that most intentionalities are highly correlated with each other and therefore can be expected to belong to a low-dimensional subspace on the semantic map.