> Getting the model to break out of that baseline without disrupting the model's ability to follow technical rules, maintain logic and reasoning, etc. is the difficult part.

Sure, that is also somewhat challenging and is necessary to get human sounding prose. However doing so is not sufficient to produce "creative" literature by any reasonable metric.

> you're again saying unsupervised then following up with descriptions that sure sound like you're referring to RL and supervised learning respectively this time.

Are you sure it isn't you who is confused about the usage of those terms? I merely suggested that both preparing and making use of labeled data (ie supervised learning) seemed like it would prove quite difficult here. Quoting from wikipedia (https://en.wikipedia.org/wiki/Unsupervised_learning):

> Unsupervised learning is a framework in machine learning where, in contrast to supervised learning, algorithms learn patterns exclusively from unlabeled data.