I am building a graph memory too, and I agree with you. It is almost useless to generate triplets, and instead generate nodes that are usually statement strings. And can extend up to a short paragraph too.

I have strong opinions that memory should be a graph + vector hybrid. The vector store can store and index information as a cognitive fragment( ex. all things related to my house), and can keep editing it as a set of statements, while that node can be associated with other nodes (ex. my renovation plans, budgeting, etc.), because those are separate fragments. I am also using LLM to consolidate and find new patterns across the connected memories

> But one problem I see with these memory systems is that they can reduce interest on a topic once we put it in the KB.

Can you elaborate please?