sounds like you have some insight? I work in biology and my fellow scientists keep talking about knowledge graphs and the only use I can see for it is better RAG answers, and even then its use seems rather limited there
ngl I think knowledge graphs are not really prime-time ready. Maybe if you have one already existing, you can use an LLM to query your knowledge graph with templates or text-to-cypher. But letting an LLM traverse a graph is not really feasible (slow and expensive)
If you don't have an existing knowledge graph, its not really feasible to let an LLM build one (also slow an expesnsive, and error prone)
In my opinion, vector search + keyword (or similar, like sparse vector) search + reranking will get you much further and scales much better. Add on top a little bit of query understanding (routing, question generation), and you are golden.
they can be hard -- takes a lot of manual curation, heuristics, etc. to have a good graph if you are just trying to create a graph from unstructured data
