>
> Can you give about ten examples of rules?  (That would answer a lot of my
> questions above)

That would just lead to really long list of questions that I don't have time to
answer right now....

In a month or two, we'll write a paper on the rule-encoding approach we're
using, and I'll post it to the list, which will make this approach clearer.

> Where did you get the rules?  Did you hand-code them or get them from
> somewhere?

As you know we have a system called RelEx that transforms the output of
the link parser into higher-level semantic relationships.

We then have a system of rules that map RelEx output into a set of
frame-element relationships constructed mostly based on FrameNet.

For the sentence

Ben kills chickens

RelEx outputs

_obj(kill, chicken)
present(kill)
plural(chicken)
uncountable(Ben)
_subj(kill, Ben)

and the RelExToFrame rules output

Killing:Killer(kill,Ben)
Killing:Victim(kill,chicken)
Temporal_colocation:Event(present,kill)

But I really don't have time to explain all the syntax and notation in
detail... if it's not transparent...

And I want to stress that I consider this kind of system pretty
useless on its own, it's only potentially valuable if coupled with
other components like we have in Novamente, such as an uncertain
inference engine and an embodied learning system...

Such rules IMO are mainly valuable to give a starting-point to a
learning system, not as the sole or primary cognitive material of an
AI system.  And using them as a starting-point requires very careful
design...

The 5000 rules figure is roughly rooted in the 825 frames in FrameNet;
each frame corresponds to a number of rules, most of which are related
to specific verb/preposition combinations.

Another way to look at it is that each rule corresponds roughly to a
Lojban word/argument combination... pretty much, FrameNet and the
Lojban dictionary are doing the same thing, which is to precisely
specify commonsense subcategorization frames.

-- Ben

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