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It turns out cracking the Natural Language Problem and building a General Modeling Machine intersects is "the same problem" (to a large but not total degree) since human language is a General Model Machine.  By cracking the problems created by the 424 distinct definitions of the word "set" gets you a long way to being able to provide the computer with the ability to accurately process reference-to-phenomenology - the key barrier to a GMM.

Long-winded exposition follows.

Jane bought an apple.  Jane bought a banana.  Jane has two fruit.

And one must ask: where the hell did "fruit" come from?

Well, once you put an apple and a banana in a bag (a collection, technically) the reference-to-phenomena is an Emergent: fruit.  One can, of course, list all the members of the collection, but nobody will tolerate:

Jane went to the apple, banana, pear, orange, mango, pineapple, lemon, lime, kiwi, and plum store and asked the apple, banana, pear, orange, mango, pineapple, lemon, lime, kiwi, and plum seller if he had any tomatoes for sale at his apple, banana, pear, orange, mango, pineapple, lemon, lime, kiwi, and plum stand because a tomato is a member of the apple, banana, pear, orange, mango, pineapple, lemon, lime, kiwi, and plum Set.

for long.  And we don't:

Jane went to the fruit stand and asked the fruit seller if he had tomatoes for sale at his fruit stand because a tomato is a fruit.

Excluded Middle Set Theory cannot deal with this very easily.  In fact there's a (highly paid, incredibly tedious) specialty within IT beavering away to solve the problems encountered by using Excluded Middle Set Theory (aka, Relational Database Model) in a Inclusive Middle World.  Because ..

The apple in "the apple of my eye" is not the same "apple" that, supposedly, bonked Newton on the noggin and the "fruit of one's loins" is not a kumquat.  

The practical result for a NLP or GMM is, using standard & approved CompSci procedures the Robert Frost couplet:

but I have promises to keep,
and miles to go before I sleep

has around 4.3 trillion possible combinatorial meanings and would take over 6,000 years to run through them all to find which one is the one you want.  Further you then throw all that processing away because it tells you nothing about how to process:

But I promise sleep before the miles to keep

(which is bad poetry ... and gets the point across) due to the fact the approved CompSci procedures used to parse the utterance (first step) throws all the "meaningfulness" away, (second step) constructs a representation of the "meaning" and then goes (third step) laboriously stumbling around trying to find the "meaning."

The project I've been working on for donkey's years started out assuming (silly fools we) "but I have promises to keep" is a pretty goddamn good representation of the meaning of "but I have promises to keep" and if you keep the "meaningfulness" in the first step you don't have to go looking for it in the third step.

From such stunning insights doth leaps in Human Civilization depend.

   

She believed in nothing; only her skepticism kept her from being an atheist. -- Jean-Paul Sartre

by ATinNM on Fri Aug 26th, 2011 at 09:34:59 PM EST
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