zlacker

>>iafish+(OP)
I wonder what is the closest thing to Cyc we have in the open source realm right now. I know that we have some pretty large knowledge bases, like Wikidata, but what about expert system shells or inference engines?

>>mepian+pe
OWL and SPARQL inference engines that use RDF and DSMs - there are LISPy variants like datadog still kicking around, but there are some great, high performance reasoner FOSS projects, like StarDog or Neo4j

https://github.com/orgs/stardog-union/

Looks like Knowledge Graph and semantic reasoner are the search terms du'jour, I haven't tracked these things since OpenCyc stopped being active.

Humans may not be able to effectively trudge through the creation of trillions of little rules and facts needed for an explicit and coherent expert world model, but LLMs definitely can be used for this.

>>observ+6h
You can actually do "inference" or "deduction" over large amounts of data using any old-fashioned RDBMS, and get broadly equal or better performance than the newfangled "graph" based systems. Graph databases may be a clear win for very specialized network analysis, but that is rare in practice.

>>zozbot+ek
Graph databases win in flexibility and ease of writing the queries over graphs, honestly.

Of course the underlying storage can be (and often is) a bunch of specially prepared relational tables.

But the strength in graph databases comes from restating the problem in different way, with query languages targeting the specific problem space.

Similarly there are tasks where SQL will be plainly better.

>>p_l+cl
Every time I try to write a query for GitHub’s graphql API I lose a few hours and go back to rest. May be it’s easy if all the edges and inputs are actually implemented in ways you would expect.

>>totets+fp
GraphQL isn't exactly a proper graph database query language. The name IIRC comes from Facebook Graph API, and the language isn't actually designed as graph database interface.