There are several frameworks that have been built by both linguists and computer scientists to deal with the problem of semantic representation of sentences, most notably Abstract Meaning Representation (https://amr.isi.edu/), Framenet(https://framenet.icsi.berkeley.edu/), PropBank. However, AMR explicitly only provides representations of sentences, and PropBank deals with the sort of predicate-argument structures which effectively are bound within a sentence.
There has also been research in NLP in determining basic relationship categories between sentences - whether one entails, paraphrases, or contradicts another one. However, most paragraphs contain sentences with much richer relationships.
Has anyone come up with a way of reasoning about the semantics of a paragraph, as opposed to a sentence, that lends itself to developing annotation tools and datasets? For instance, let's say I perform AMR parsing and then have a list of graphs, each of which represents a sentence - is there any other data structure I could transform this into which would be more useful than just a list of graphs which I know are somehow related?
I guess a more theoretical question would be - are paragraphs semantically just the union of all the propositions in each sentence, or is there more internal structure?