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I ended up throwing the README at an LLM and it gave me a much simpler and clearer explanation. Copying the bits of an explanation that helped me:

> The problem it’s trying to solve is that generating valid SQL doesn’t necessarily produce the right answer. An AI might find a column called revenue, but still choose the wrong dataset or misunderstand whether that figure includes things like refunds. Auto Ontology adds information about what the data means to help it make those decisions.

and then the one paragraph summary at the end:

> My reading: it’s a database chat application built around a reusable catalogue of business meaning. The question worth testing is whether that catalogue makes answers measurably more correct—and how much human work it takes to get the definitions right.

by throwaway575216 minutes ago|

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I could easily solve it myself, but the point is that I don't need to spend my valuable time on a project that the author's done care enough about to give a proper readme. And semantic web/graph indexers and queriers are not new, even if there are new tools at our disposal for classifying and querying ontological structures.

If they can't do that, it's a signal they didn't care enough about the details to rely on this project, and there is more cool software than ever I can spend my finite time on.

That may not be particular fair, and it may be a great project, but the bar is just much higher now.

by gavinray1 hours ago|

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I had to go digging into the source to realize what it was, e.g.

https://github.com/NVIDIA/auto-ontology/blob/main/auto_ontol...