Categorical Organization in Memory: ChatGPT Organizes the 665 Topic Tags from My New Savanna Blog

Abstract

I gave ChatGPT three lists of topics for which it had to propose categories into which the topics could be sorted. Two lists were relatively short, 56 and 53 topics; I asked ChatGPT to propose six organizing categories for each. One list was much longer, 655 topics; I asked ChatGPT to propose 12 for categories for it. In all cases the proposed categories were reasonable. ChatGPT explained each proposed category either with a pair of sentences (the short lists), or with characterizing phrases (the long list). These characterizations were reasonable. In a further task, when asked to place topics under the proposed categories, ChatGPT placed many topics under the first two categories and very few under the last two. Though quite different in detail, this task has a rough formal similarity to generating a coherent story that is organized on three levels: 1) the whole story, 2) story segments, 3) sentences in story segments.

Keywords: ChatGPT,LLM,transformer,deep learning, semantics, categories, semantic ontology,machine learning