The obvious start seems to be having separate fiction and nonfiction LLMs and not training the nonfiction ones on Archive Of Our Own. People also end up confused about the truth when nobody points out the difference between fiction and nonfiction.
The obvious answer then is to tell it to make sure that what it's finally outputting is really part of the "real" API, but I think it's safe to say there's some technical hitch there, as it's safe to say OpenAI probably spent quite a lot of energy trying to solve the code hallucinations, and ultimately was unable to do so. I'd guess that the more you restrict its recombination ability, the more you end up with it inappropriately (and incorrectly) just regurgitating large chunks of its training input verbatim. Basically it becomes more like a keyword hunting search engine, and less like a generative LLM.
How about an economics textbook, or an article in the economist? "A history of the english speaking peoples" by Winston Churchill?
If we restrict to "ground truth we feel very sure about" it feels like available training data might be quite small.
And anyway - answers to all my ‘fictional facts’ questions above can be sourced from Wikipedia - there’s tons of made up stuff on there.
Hint: how many stadiums are filled with people standing up to recite a newspaper article about a battle in the War of 1812?