Build real-time knowledge graph for documents with LLM

I feel like you can do the same using a single markdown file and an LLM (e.g. Claude Code).

I do it that way and then I hooked it up with the Telegram API. I’m able to ask things like “What’s my passport number?” and it just works.

Combine it with git and you have a Datomic-esque way of seeing facts getting added and retracted simply by traversing the commits.

I arrived to the solution after trying more complex triplets-based approach and seeing that plain text-files + HTTP calls work as good and are human (and AI) friendly.

The main disadvantage is having unstructured data, but for content that fits inside the LLM context window, it doesn’t matter practically speaking. And even then, when context starts being the limiting factor, you can start segmenting by categories or start using embeddings.

Why not merely upload all relevant documents into Gemini? Split the knowledge into smaller knowledge domains and have agents ( backed by Gemini) for each domain?

Now imagine it with theorems as entities and lean proofs as relationships

People probably don't discuss the problems enough about an open world knowledge graph. Essentially the same class of problems as spam filters. Using an open language model to produce a graph doesn't create a closed world graph by definition. This confusion as well as just general avoidance of measuring actual productivity outcomes seems like an insurmountable problem in knowledge world now and I feel language itself is failing at times to educate on this issues.

idk if it’s precisely the same but o3 recently offered to create one for me in, was it markdown?, recently. suggesting it was something it was willing to maintain for me.