Abram,
The syntactic surface feature argument makes a good, but rather narrow, addition
to the list of mechanisms that can engender a "feeling of not knowing." The
interesting part is that, as someone who speaks Norwegian, using that word in
the example didn't set off phonological feature alarms for me. Non-Norwegian
speakers picked it up right off.
Your argument for semantic (i.e., meaning) features lacks concrete examples so
it is difficult to tell exactly what you mean. Based on your general argument,
I would conclude that it requires a content search of some sort and, therefore,
falls under one of the mechanisms posited in my initial post.
Cheers,
Brad
Abram Demski wrote:
I think the same sort of solution applies to the world series case;
the only difference is that it is semantic features that fail to
combine, rather than syntactic. In other words, there are either zero
associations or none with the potential to count as an answer.
--Abram
On Tue, Jul 29, 2008 at 7:51 PM, Brad Paulsen <[EMAIL PROTECTED]> wrote:
Matt,
I confess, I'm not sure I understand your response. It seems to be a
variant of the critique made by three people early-on in this thread based
on the misleading example query in my original post. These folks noted that
an analysis of linguistic surface features (i.e., the word "fomlepung" would
not "sound right" to an English speaking query recipient) could account for
the "feeling of not knowing." And they were right. For queries of that
type (i.e., queries that contained foreign, slang or uncommon words).
I apologized for that first example and provided an improved query (one that
has valid English syntax and uses common English words -- so it will pass
linguistic surface feature analysis). To wit: "Which team won the 1924
World Series?"
Cheers,
Brad
Matt Mahoney wrote:
This is not a hard problem. A model for data compression has the task of
predicting the next
bit in a string of unknown origin. If the string is an encoding of natural
language text, then
modeling is an AI problem. If the model doesn't know, then it assigns a
probability of about
1/2 to each of 0 and 1. Probabilities can be easily detected from outside
the model, regardless
of the intelligence level of the model.
-- Matt Mahoney, [EMAIL PROTECTED]
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