I test LLMs on the plot details of Japanese Visual Novels. They are popular enough to be in the training dataset somewhere, but only rarely.
For popular visual novels, GPT-4 can write an essay, 0 shot, and very accurately and eloquently. For less popular visual novels (Like maybe 10k people ever played it in the west). It still understands the general plot outline).
Claude can also do this to an extent.
Any lesser model, and its total hallucination time, they can't even write a 2 sentence summary accurately.
You can't test this skill on say Harry Potter, because it appears in the training dataset too frequently.
I am surprised there isn't enough fan fiction et al in the training set to throw out weird inaccuracies?
Surely the most logical things to train on would be all the fandom.com Wikis. They're not verbatim, but they're comprehensive and fairly accurate synopses of the main plots and tons of trivia to boot.
Bing Chat absolutely shut me down right away, and would not even continue the conversation when I insisted that it get into character.
ChatGPT would seem to agree and then go on merrily ignoring my instructions, answering my subsequent prompts in plain, conversational English. When I insisted several times very explicitly, it finally dropped into a thick, rich, pirate lingo instead. Yarr, that be th' wrong sort o' ship.
Bard definitely seemed to understand who Eddie was and was totally playing along with the reference, but still could not seem to slip into character a single bit. I think it finally went to shut me down like Bing had.