Developer Tests Jev Probability Tool Against LLMs for Classifying Cinema Listings

A developer behind Clusterflick, a London cinema listings aggregator, has been using a language model for over a year to categorise 450–600 daily listings into one of ten types, such as movie, talk, or event. The task is complex because many listings, like a Buster Keaton society screening at the Cinema Museum in Kennington, do not fit neatly into a single category. The developer recently trialled Jev, a non-generative tool that returns probability distributions over structured options rather than producing text. Unlike the LLM approach, Jev evaluates multiple yes/no questions in parallel within a single request, allowing underlying classification factors to be tested directly. The experiment explored whether Jev could match or improve on a year's worth of prompt refinement, given that the text explanations produced by the LLM were never actually used.