We used OpenAI’s Batch API (OpenAI, n.d.) to obtain the list of keywords for each frame generated by GPT-4o mini; LLaVA, on the other hand, was run locally. As a result, we extracted 3730 frames from the documentary and obtained two lists of keywords for each frame. We then used topic modelling to process the keywords. This approach avoided some of the pitfalls of LLMs as black boxes, because topic modelling is an established and mathematically proven technique. We used Gensim’s implementation of Ensemble LDA (Brigl, 2019) to run multiple topic models simultaneously, keeping only the topics consistent across several topic models, thereby reducing the number of incoherent topics.