Prompts are a great place to look for these, but the part you linked too isn't very important for knowledge graph generation. It is doing an initial semantic breakdown into more manageable chunks. The actual entity and fact extraction that actually turns this into a knowledge graph is this one:

https://github.com/OpenSPG/KAG/blob/master/kag/builder/promp...

GraphRAG and a lot of the semantic indexes are simply vector database with pre-computed similarity edges which does not allow you to perform any reasoning over (the definition and intention of a knowledge graph).

This is probably worth looking at, its the first opensource project I've seen that is actually using LLMs to generate knowledge graphs. This does look pretty primitive for that task but it might be a useful reference for others going down this road.