I hit "send" too soon, without finishing the thought:
On Fri, Nov 16, 2018 at 3:02 PM Linas Vepstas <[email protected]>
wrote:
> For example, this parse makes sense, and seems right:
>
> +-------->WV------->+
> +---->Wd-----+ |
> | +Ds**c+-Ss*s-+---Pa--+
> | | | | |
> LEFT-WALL the dog.n was.v-d black.a
>
> but there is another possibility, that kind-of makes sense (and perhaps
> language learning will find):
>
> +---->Wd---->+
> | +-->adjcomp--->+
> | +Ds**c+ +<-cop<-+
> | | | | |
> LEFT-WALL the dog.n was black
>
> Here, adjcomp is "adjectival compliment" and "cop" was copula. Some
> dependency grammars draw this graph. Some call it "predicative adjectival
> modifier". Lets quibble. Note that I did not draw an arrow from subject to
> verb. I could, I suppose. Note that it is now IMPOSSIBLE to draw an arrow
> from root/left-wall to the verb, because it would require a
> link-crossing, it would have to cross over the adjcomp arrow.
>
> Thus, if you want to draw an arrow from root to head-verb, and also get a
> planar graph, you are not allowed to draw the adjcomp/predadj arrow. That
> helps explain what LG does.
>
> It also helps make clear that the no-links-crossing constraint is
> imperfect. It seems reasonable, but clearly, there is a violation in the
> above rather
> trivial sentence!
>
OK, to finish this thought. Let us speculate what an MST parse of this
sentence might be like. It depends on the MI values for the word-pairs
MI(dog,was) MI(was,black) and MI(dog,black) I don't know what these are,
but clearly they will be different for a corpus of kids-lit, than a corpus
of math texts.
Next question: what happens when words are sorted into categories? What is
MI(dog, some color)? What is MI(some animal, some color)? What is
MI(physical object, some color)?
I don't have a good story here, except to say that copulas and predicative
adjectives prsent maybe the simplest-possible example of a difficulty of
moving from surface syntax (SSynt, what LG does) to deep syntax (DSynt,
what MMT does). Yet, this move is a critical one.
I'm currently thinking of it as a graph-write rule, that converts the SSynt
graph into a PLN graph
EvaluationLink
PredicateNode "has color"
ListLink
Concept "dog"
Concept "black"
Or, perhaps as Nil might like to write:
LambdaLink
VariableList
Variable $PHY
Variable $COL
AndLink
EvaluationLink
PredicateNode "has color"
ListLink
Variable $PHY
Variable $COL
InheritanceLink
Variable $PHY
Concept "physical object"
InheritanceLink
Variable $COL
Concept "color"
Of course, even the above representation is wrong, in several ways, but
nit-picking it at this stage is counter-productive.
The question is: given a learned grammar, with statistics, how to we get to
the DSynt or the opencog variant? Well, the now-quite-old Dekang Lin DIRT
paper, and the newer-but-still-old Poon&Domingos unsupervised learning
paper show the way.
Onward ho!
Linas
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