[jandrewrogers]

As the article itself points out, this has been around for 25 years. It isn’t an accident that nobody does things this way, it wasn’t an oversight.

I worked on semantic web tech back in the day, the approach has major weaknesses and limitations that are being glossed over here. The same article touting RDF as the missing ingredient has been written for every tech trend since it was invented. We don’t need to re-litigate it for AI.

[rglullis]

I would be very interested in reading what you think it can't work. I am inclined to agree with the post on a sibling thread that mentions that the main problem with RDF is that it is been captured by academia.

[FrankyHollywood]

The article states "When that same data is transformed into a knowledge graph"

This is a non-trivial exercise. How does one transform knowledge into a knowledge graph using RDF?

RFD is extremely flexible and can represent any data and that's exactly it's great weakness. It's such a free format there is no consensus on how to represent knowledge. Many academic panels exist to set standards, but many of these efforts end up in github as unmaintained repositories.

The most important thing about RDF is that everyone needs to agree on the same modeling standards and use the same ontologies. This is very hard to achieve, and room for a lot of discussion, which makes it 'academic' :)

[bfuller]

>This is a non-trivial exercise. How does one transform knowledge into a knowledge graph using RDF?

by using the mcp memory knowledge graph tool, which just worked out of the box for my application of turning forum posts into code implementations.

[ricksunny]

Link? I'm still new to mcp so forgive me if this is trivially uniquely found using your keywords.

[4ndrewl]

IME it's less than a "capture", more that most outside of academia don't have the requisite learning to be able to think in the abstract outside of trivial examples.