Comment by ammar_x

My "trick" was to divide things into batches (which can be big with LLMs with larger context sizes) and classify the items in each batch, then take the resulting categories from each batch and feed them into an LLM to group semantically similar categories into groups with a representative category for each group. The representative category can be chosen from the group or created by the LLM. This is an over-simplification of the process but that's the gist of it.