Long time lurker here.
If I understand you, Steve, your are saying (among other things) that
English is less polysemous and pragmatically less complicated than, say,
Russian. Is English your L1? Do you speak Russian? If English is indeed
your first language, it is perhaps not surprising that English seems
more semantically precise or "straightforward," as -- short of being a
trained linguist -- you wold have less meta-awareness of its nuances.
It's not as if the Arabic and Russian examples you provide have no
English analogs.
-Christopher Carr
Steve Richfield wrote:
Mike,
On 12/1/08, *Mike Tintner* <[EMAIL PROTECTED]
<mailto:[EMAIL PROTECTED]>> wrote:
I wonder whether you'd like to outline an additional list of
"English/language's shortcomings" here. I've just been reading
Gary Marcus' Kluge - he has a whole chapter on language's
shortcomings, and it would be v. interesting to compare and analyse.
The real world is a wonderful limitless-dimensioned continuum of
interrelated happenings. We have but a limited window to this, and
have an even more limited assortment of words that have very specific
meanings. Languages like Arabic vary pronunciation or spelling to
convey additional shades of meaning, and languages like Chinese convey
meaning via joined concepts. These may help, but they do not remove
the underlying problem. This is like throwing pebbles onto a map and
ONLY being able to communicate which pebble is closest to the intended
location. Further, many words have multiple meanings, which is like
only being able to specify certain disjoint multiples of pebbles,
leaving it to AI to take a WAG (Wild Ass Guess) which one was intended.
This becomes glaring obvious in language translation. I learned this
stuff from people on the Russian national language translator project.
Words in these two languages have very different shades of meaning, so
that in general, a sentence in one language can NOT be translated to
the other language with perfect accuracy, simply because the other
language lacks words with the same shading. This is complicated by the
fact that the original author may NOT have intended all of the shades
of meaning, but was stuck with the words in the dictionary.
For example, a man saying "sit down" in Russian to a woman, is
conveying something like an order (and not a request) to "sit down,
shut up, and don't move". To remove that overloading, he might say
"please sit down" in Russian. Then, it all comes down to just how he
pronounces the "please" as to what he REALLY means, but of course,
this is all lost in print. So, just how do you translate "please sit
down" so as not to miss the entire meaning?
One of my favorite pronunciation examples is "excuse me".
In Russian, it is approximately "eezveneetsya minya" and is typically
spoken with flourish to emphasize apology.
In Arabic, it is approximately "afwan" without emphasis on either
syllable, and is typically spoken curtly, as if to say "yea, I know
I'm an idiot". It is really hard to pronounce these two syllables
without emphases, but with flourish.
There is much societal casting of meaning to common concepts.
The underlying issue here is the very concept of translation, be it
into a human language, or a table form in an AI engine.. Really good
translations have more footnotes than translation, where these shades
of meaning are explained, yet "modern" translation programs produce no
footnotes, which pretty much consigns them to the "trash translation"
pile, even with perfect disambiguation, which of course is impossible.
Even the AI engines, that can carry these subtle overloadings, are
unable to determine what nearby meaning the author actually intended.
Hence, no finite language can convey specific meanings from within a
limitlessly-dimensional continuum of potential meanings. English does
better than most other languages, but it is still apparently not good
enough even for automated question answering, which was my original
point. Everywhere semantic meaning is touched upon, both within the
wetware and within software, additional errors are introduced. This
makes many answers worthless and all answers suspect, even before they
are formed in the mind of the machine.
Have I answered your question?
Steve Richfield
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