Hi.
What about using "baby English" instead of an artificial language?
That seems to be good for experiments, but unluckily it does not seem to
have the benefits of real natural language, as there is neither a big body
of text written in baby English nor many people wanting to talk it to a machine.
- Artificial languages are designed to be processed (translated or compiled) in
the order:
lexical tokenization, syntactic parsing, semantic extraction.
That is mostly true, but more and more artificial languages start to mix parsing
and semantics. Perhaps these should be called semi-artificial? But anyway,
what I have in mind are mostly programming or specification languages,
these feel a lot more artificial than Lobjan or Esperanto.
This does not work for natural language. The correct order is the order in
which
children learn: lexical, semantics, syntax.
I strongly disagree with this "correct order". First of all, the
stages are all concurrent,
there are great experimental difficulties in children research and
large differences
between (a) what children understand and what they produce, (b) cultures and
nationalities and even (c) single children. If you insist on giving any order,
I'd rather say that semantics is there even before lexical part and in
many cases
you are compelled to say that language structure ("syntax") comes before the
lexical part (what I have in mind is that many children first learn
the melody of
language and only later words, you can sometimes hear them make full, very
convincing conversations before they master pronunciation of all consonants).
Artificial languages have no such mechanism and cannot tolerate ambiguity or
errors.
This improved a bit in recent years. For example you can take a look at
Attempto Controlled English (http://www.ifi.unizh.ch/attempto/) - it's a formal
language translated to first-order logic, but resolves anaphoric references and
some other context-related things.
Artificial languages must be processed by fixed algorithms.
Fixed algorithms are only as fixed as the mind of the programmer. There
are modern formal languages that add new syntax with each declaration.
For example you can define a new grammatical rule for each new function
or constructor you declare. This is possible, starts being done and seems
to have nothing to do with fixed algorithms.
Learning algorithms are unknown.
Well, learning grammar rules is very well known. I think it was even used
for learning regular-expression translators for languages a few decades ago.
Learning more complex things, as context dependency, is more difficult but
is quite an active area of research and many algorithms are known, even if
none of these is prefect or good enough for natural language on the web.
- Writing in an artificial language is an iterative process in which the output
is checked
for errors by a computer and the utterance is revised. Natural language uses
both
iterative and forward error correction.
Error correction in artificial languages can be though of as similar to asking
additional questions to understand a statement in natural language. There
is an interaction going on in both cases. Just our programming languages have
very bad manners and report errors in horrible ways, but that's another problem.
With these arguments I do not want to convince you that artificial languages
are getting near the natural ones in ease of use, as this unluckily
does not seem
to be the case. But we are getting better in user-friendliness of
artificial (formal)
languages and add features like context-dependency, dynamic grammar learning
or better interaction for disambiguation and error correction. My point is
that even with all these features, our formal languages still feel
very unnatural,
and it seems this is because the _underlying semantic representation_ is not the
one we consider natural. And I really doubt that you can create a language that
will feel natural without first working a lot on what it will be
translated to and
first getting that at least more or less right. What do you think?
- lk
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