From what I’ve gathered, it doesn’t work at all like a normal classifier. As in, for a classifier you’d train it for a specific task to reduce the cross entropy. So, in a hand-wavy way “the model knows the truth”. For Jev-type models it’s more like an LLM, in the sense that the “truth” is in the context you provide. But instead of producing a completion it fills in the schema. But it’s always - “given the context, the schema needs to be filled in like this”