Grammar with a G

[david_tuggy at SIL.ORG]

Rob Freeman wrote (in response to me):

****
This looks to me like the approach traditionally followed in the application of
e.g. Neural Networks to language. The key assumption is that the structure you
need to find is finite [...]

My view is that this assumption of a finite number of key patterns in the data
to be extracted as rules is a mistake. I think there are many generalizations
which can be made about the data and we need to be able to get to any, or any
level, of them. [...]

I see the classes, the possible groupings, as being directly synonymous with
meaning (an 'organization of experience') not as just some finitely
characterizable structural step on the way to meaning. [...]

you will find any number of regularities, which will be synonymous with the
multiplicity of 'grammars'. But any one of these will only ever be one slice of
the subtlety of structure, and thus meaning, of which the language is capable
through collections of examples. [...]


So, in conclusion, you have put your finger on what I think has been the
big problem with analogical models of language hitherto. They have been looking
for finite classifications of the data they seek to model. Essentially still
trapped by the generative grammar style of thinking about language system. We
need to start to see syntactic structure as vectors of examples pointing to
meaning, not as algebras of finite abstractions, then we will know what to do
with our networks.
****

What did I say about finitude? (I wasn't aware of putting my finger on anything.
Moral, don't stick your finger in the pie unless you want to risk putting it on
something ?)

If I understand what you're talking about, you're saying there is no
predetermined number of relevant patterns (-schemas-rules), that even logically
inconsistent patterns may coexist, that patterns of all levels of generality or
(un)systematicity may be relevant, that the patterns themselves are meaningful
and that the establishing of a pattern is establishing meaning, that low-level
(highly detailed) patterns have some sort of priority over high-level (more
general) ones, and so forth. If that's what you're after, Langacker's model has
it all built in.