There's a really interesting cross-over here with literary structure. You need to teach a model to recognize tone, theme, and setting in addition to world "facts."

What makes a world like Westeros different than the Shire isn't just facts like "seasons are really long" but elements of tension, political unrest, and the outlook of the people who inhabit it. To do this effectively, you need to be building simulations of literary works. There's always going to be an art to this, but instead of the manuscript, it's going to be about the parts of the model.

I think in the context of natural language for game worlds, "prose" is targeting the much lower bar of something that sounds like a human might write it, vs like "you PLACED KEY in THE LEFT DOOR. Proceed to A STAIRCASE" from games of yore. Understanding the much richer space of literary prose, such as the difference between the Shire and Westeros, seems like a harder problem, but also one that might be well suited for existing NLP training pipelines, because you can label a large amount of text with only a few descriptors. It might be tough to come to a consensus amongst literary experts what those descriptors should be, but e.g. if LOTR book 1 is "pastoral" and ASOIAF book 1 is "gritty", you've now got a lot of text associated to each of those labels. I wonder if anyone is working on this?

SHRDLU was a simple world you could manipulate with English prose back in the 1960s.

https://en.wikipedia.org/wiki/SHRDLU

Unless you feel you need flowery expressive input as well as output. But do we really need input more sophisticated than that of Zork here?