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What underlying principle is at play for how objective or subjective a natural language instruction is?

I am interested in exploring a series of prompts for a large language model which move from instructions which have a clear-cut "correct result", such as the instruction to capitalize every letter "S" in some sentence, to questions which may have a few acceptable results, to questions which are more open-ended and subjective.

I would like to think of some analytical framework which makes it clear exactly what is changing, presumably semantically, as we shift along that gradient. I can't see it clearly in my mind at the moment.

My guess is it could be modeled using information theory, and I can expand on how.