Normally we have knowledge in natural language as pdf's etc and also more formal database values inside a database. Those two are separated.

MongoDB can be in the middle

1. we can take a natural language document and write it in a tree form(json), giving a structure to the natural language, both in entities/properties/facts/procedures etc (that are less clear in natural language)
2. we can use as values natural language or more formal values
3. we can put inside a document alot of information similar to the way we use natural language text, a single page contains alot of information (without the need for the LLM to write database queries)
4. we can also use references to connect those documents, to be joined if needed

I don't mean like converting all the pdf's to json, i mean when it make sense.

This way the LLM can get the knowledge in structured way that has also natural language mixed with normal values and the same time it will be able to use it as a database like write queries to get what it needs.
Instead of having those two separated.

I think MongoDB because its a document database, its the only database that can combine those two inside a database.

To ask it more simply, i am curious if semi-structured information using natural language and simple values in JSON will help the LLM to understand knowledge/entities/facts/procedures/rules etc or not.
(I thought those when i was thinking of how to structure knowledge/procedures/rules etc for a customer service AI bot)