The training used in the current round of image generators is Contrastive learning - the idea is that you don't use "properly curated" datasets - you just throw volume at the problem and let it sort itself out. Which makes sense - humans learn by the same mechanism.

The LAION-5B set in particular is filtered by it's CLIP embeddings - basically run a better AI to classify the images, and check that the two descriptions rate highly enough for similarity, which in turn lets the system have some confidence an image isn't completely wrong (also the step you filter out NSFW and other things if you want, generally).