Communications on a
National Project
Next-Wave Publishing, Part 3: Revolution in Context –
Seybold Publications Vol 3, Number 23
Posted for Scholarly Review Only
3/12/2004 12:37 PM
Paul,
Following are my comments on the
Seybold report, which I sent to Dick Ballard's cc list.
Sorry for any duplication.
And please note that my comments
are *NOT* about natural language, but about the semantics of any representation
whatever -- including triples or anything else.
John Sowa
**
Dick,
Thanks for sending the report. I hate to say nasty things about people
who say nice things about my work, but I can't endorse that report. Following are some comments.
The first point is that the authors
fail to recognize that the ambiguities of natural language are intimately
related to semantics and that changing the notation does nothing to solve
them. The following point is not
only wrong, but totally wrong headed:
from ambiguities inherent in
natural language.
We contrast language-based
knowledge representation
with semantic-form
declarative knowledge and conclude
that semantics trumps
linguistics.
As I have said repeatedly, SYNTAX IS NOT THE PROBLEM. Therefore, no change to syntax can ever solve the problem.
I certainly agree that there are
ambiguities in natural languages. The simple, trivial ambiguities are
syntactic. They are easy to deal
with. The difficult problems are
all in the semantics. And nothing
that the authors say in that report comes to grips with the real semantic
problems or even acknowledges their existence.
The following sentence indicates
the authors' starry-eyed innocence:
As the semantic model
becomes richer, it more
completely specifies not
only the formal class-subclass
relationships, but also
relationships between concepts,
and the descriptive logic
and conditional assertions
that are used to perform
inference.
That is the view that Wittgenstein adopted from Bertrand Russell in 1913, and which he elaborated in his first book, the _Tractatus Logico-Philosophicus_. After writing that book, Wittgenstein thought that he had solved all the problems of philosophy, and he retired to an Austrian village to teach elementary school. That's where he discovered that kids (and grown-ups) don't think that way. As Shakespeare said,
There are more things in
heaven and earth, Horatio,
Than are dreamt of in your
philosophy.
For the rest of his life,
Wittgenstein analyzed, recanted, and clarified the hopelessness of the
superficial approach that he and Russell had developed in their early work.
Wittgenstein’s analysis had nothing to do with the expression of concepts in
natural language or in logic.
Every problem and pitfall that Wittgenstein analyzed in his later
philosophy applies just as much to the declarative languages of logic or the
semantic web as it does to natural language.
Hope reigns eternal within the
programmer's breast:
Also, it is possible to
reuse ontologies, in whole or
in part, that have already
been developed.
I heard that same statement made about programs back in the 1960s: Once a program has been written, it could be used again by anybody else who had the same problem, and the collection of solved problems would grow indefinitely.
The key goal mentioned below has
nothing to do with the kind of language that is being used:
A key goal of language-based
knowledge representation
is to eliminate the
ambiguity of describing things
with labels and natural
language, leading to improved
search and easier
integration of content and processes.
But, as we have seen, this goal
is difficult to achieve
when we use language to
describe what we mean. Natural
language use is inherently
ambiguous. Many words have
multiple meanings. There is
no way to guarantee that
two occurrences of the same
word have the same meaning.
That makes it sound as the word "cat" in English is "inherently ambiguous", but if we write a unique identifier "cat" in a pure, unsullied declarative language, it will magically acquire a unique meaning that nobody (or no computer) could possibly confuse with anything else.
The solution that the authors
propose is the same one that Frege, Russell, and the logical positivists were
hoping to achieve with logic -- and they failed miserably:
Ultimately, the only way to
ensure precise meanings
is to move away from natural
language toward
pure semantic codes and
relationships; that is, use
unique identifiers to
identify concepts. (We may draw
an analogy here with the UPC
[universal product code]
identifier that has no
significance other than that
it is unique.) Do not use
labels or names of things.
Rather, determine meaning by
the sum of all the
relationships the concept
has.
A UPC has a unique meaning because it has been legislated to have a unique meaning. Once you have legislated the meaning, its meaning is unique in any context, linguistic or nonlinguistic (such as swiping a light pen over it).
People have been legislating
meanings for words and concepts in natural languages since the time of
Socrates. It is done all the time
for concepts in mathematics and science -- and those concepts are expressed by
"labels" or "names" in natural language sentences. That has been done repeatedly and
successfully since the time of Euclid.
But even in mathematics, where the
most precise natural language usage can be found, it is very rare for any two
mathematicians (or even any single mathematician) to use the same term in
exactly the same way in two different publications. Therefore, it is common for
mathematical publications to have an opening section (or an appendix) that
states the definitions and axioms that are assumed.
Note the lessons to be learned:
1. The only concepts that are ever precisely defined are
legislated concepts -- ones whose meanings are stipulated or agreed by
convention.
2. Those agreements can be formalized and used in natural
languages just as well as in any artificial language. That fact has been demonstrated repeatedly since the time of
Socrates and Euclid.
3. But establishing agreements that hold for more than one
context, such as one Platonic dialog, a single publication in mathematics, a
single computer program, or a single database system, is extremely difficult
and extremely rare.
4. In computer systems, the only legislated concepts that
are repeatedly used in a fixed sense are ones that are embodied in programming
code that is very hard to change, such as the kernel of an operating system,
the compiler of a programming language, or
a library of programs that are fundamental to the OS or the
compiler. Even then, those
meanings change with every release or patch to the OS or the compiler.
5. Outside of mathematics and computers, the most common
attempts to legislate meaning are in the legal system. The US Constitution is
the world's first and most successful attempt to legislate a complete system of
government and the concepts used to describe it. But that success depends
completely on the ongoing efforts to interpret, extend, and clarify those
concepts by the three branches of government (judicial, legislative, and
executive). With such a mechanism
of constant reinterpretation, the system has survived and flourished for over
two centuries. Without it, the Constitution would have been a useless piece of
paper.
Note that in every one of these
examples -- in mathematics, computer systems, and government -- the mechanism
of enforcement, interpretation, and reinterpretation of the semantics is the
*ONLY* guarantee that the concepts are used with a common meaning.
The use of a natural language or an
artificial language does not make the slightest difference in determining
whether a concept's meaning shifts or stays constant.
Summary: The Seybold article is a restatement of
a hope that Frege and Russell proposed a century ago. Wittgenstein and the logical positivists tried to achieve it
with logic, and they failed miserably.
The semantic webbers have zero chance of achieving it by replacing
natural language with any other kind of language or notation.
Bottom line: You can't solve a problem by ignoring
it.
For more about semantics and the failure of logical positivism, I recommend the following:
http://www.jfsowa.com/pubs/signproc.htm
Signs, Processes, and
Language Games
John Sowa