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I was doing lots of Prolog in the past, inspired by The Art / Craft of Prolog plus PAIP, and I also tried to find information to implement a toy Watson but ther

by nextos 5y ago

I was doing lots of Prolog in the past, inspired by The Art / Craft of Prolog plus PAIP, and I also tried to find information to implement a toy Watson but there's next to none. I even talked to some consultants from IBM about this, but all the information I could get was very vague. This might have changed in the meantime. BTW, I had seen your ILP publications in other previous posts and they are quite cool! Contrary to the popular belief, I think there is still a lot of room for logic-based approaches to AI.

YeGoblynQueenne 5y ago
Woa, thanks, you make me blush :) All the information that IBM have released about Watson (the original system that won that Jeopardy game) was spread around a dozen reports published in the "IBM Journal of Research and Deelopment". I have the lot on a drive half a continent away, otherwise I'm sure it would be OK to share them. You might be able to find them online, but a very quick look didn't locate them for me. Online versions might be accessible from a university library, although I don't even remember their titles. In short, from memory, Watson started with a shallow parse that was then used to fill in good old frames. If I remember correctly those were then queried by the Prolog rulebase. The shallow parse was by means of a dependency grammar trained from an annotated corpus (so not a language model, say). That's the very high level of it- I read all that back in 2014 or so and I only half-understood it. I seem to remember that one of the reports made a big to-do about a shallow parse being sufficient to solve a good chunk of information retrieval problems.