[tannhaeuser]

Here's the first paragraph of that article:

> The Big Picture: Knowledge graphs triple LLM accuracy on enterprise data. But here’s what nobody tells you upfront: every knowledge graph converges on the same patterns, the same solutions. This series reveals why RDF isn’t just one option among many — it’s the natural endpoint of knowledge representation. By Post 6, you’ll see real enterprises learning this lesson at great cost — or great savings.

If you really want to continue reading and discuss this kind of drivel, go ahead. RDF the "natural endpoint of knowledge representation" right. As someone having worked on commercial RDF projects at the time, after two decades of pushing RDF by a self-serving W3C and academia until around 2018 or so, let's say I welcome people having come to their senses and are back at working with Datalog and Prolog. Even as a target for neurolinguistics and generation by coding LLMs does SPARQL suck because of its idiosyncratic, design-by-comittee nature compared to the minimalism and elegance of Prolog.