Books

LLMs don't really know the subject matter they talk about in the same way a person does. Whatever you feed as input biases the responses towards and away from certain sequences of words. If you put in something about Star Wars, it'll weigh its output in favor of saying things like "Luke Skywalker" and "Darth Vader" and away from things like "The best way to use a crockpot is...". When you're trying to get it to recall facts about things that aren't extremely famous, it will jumble some parts or just make things up that sound plausible.

As an example, I liked to prompt them with "Tell me about 'A Valiant Effort (1989)'" as a test -- it doesn't actually exist, but they'd often tell me it was a painting or a movie or an obscure book with hallucinated details until very recently; newer models seem more likely to say "I don't know what that is" or similar, but that's not guaranteed.

To get better results, try feeding it a passage you'd like it to work on directly in the input instead of assuming it just knows the story already, and you'll get output weighted by the actual text (and whatever else you put in context).