That's just general context rot, and the models do all sorts of off the rails behavior when the context is getting too unwieldy.
The whole breakthrough with LLM's, attention, is the ability to connect the "not" with the words it is negating.
The whole breakthrough with LLM's, attention, is the ability to connect the "not" with the words it is negating.
Like, in Latin, the verb is at the end. In that, it's structured like how Yoda speaks.
So, especially with Cato, you kinda get lost pretty easy along the way with a sentence. The 'not's will very much get forgotten as you're waiting for the verb.