[bobbylarrybobby]

IIRC IBM’s Watson (the one that played Jeopardy) used primitive NLP (imagine!) to form a tree of factual relations and then passed this tree to construct Prolog queries that would produce an answer to a question. One could imagine that by swapping out the NLP part with an LLM, the model would have 1. a more thorough factual basis against which to write Prolog queries and 2. a better understanding of the queries it should write to get at answers (for instance, it may exploit more tenuous relations between facts than primitive NLP).

[YeGoblynQueenne]

Not so "primitive" NLP. Watson started with what its team called a "shallow parse" of a sentence using a dependency grammar and then matched the parse to an ontology consisting of good, old fashioned frames [1]. That's not as "advanced" as an LLM but far more reliable.

I believe the ontology was indeed implemented in Prolog but I forget the architecture details.

______________

[1] https://en.wikipedia.org/wiki/Frame_(artificial_intelligence...

[baq]

Please tell me that's approximately what Palantir Ontology is, because if it isn't, I've no idea what it could be.

[UltraSane]

https://www.palantir.com/docs/foundry/ontology/overview/