SUO: Re: Enhancing Data Interoperability with Ontologies...
John,
That's the critical point:
JB> There are some obvious reasons for this:
> anaphora resolution relies heavily on real-world
> knowledge and that is not available in great
> quantities for the anaphora resolution
> algorithms. The standard techniques of picking
> the most likely referents work pretty well (in
> fact very well), but there is always that small
> residue on top that they currently miss.
Natural languages have evolved for use by
people who apply both syntactic and semantic
knowledge to interpret a text. Some NL
processors have achieved a fairly good level
of accuracy by using syntax alone, and some
have achieved a fairly good level by using
mostly semantics with a modest amount of syntax.
But in general, both are needed.
Even so, no NL processor (human or computer)
can ever achieve 100% reliability on every text
thrown at it because nobody (human or computer)
is omniscient. And even if the reader is
very well versed in the subject matter, there
is no guarantee that the author has written
crystal-clear prose that eliminates all
conceivable misinterpretations (as we have
all seen in numerous email exchanges).
Therefore, no NL processor can ever achieve
100% reliability. However, it is also important
to realize that the supposedly unambiguous
artificial languages (logic, controlled NLs,
or any programming language ever invented)
are just as unreliable -- but the authors
are usually blamed rather than the readers.
Fundamental principle: A formally precise
language can give no assurance of reliability
because what it says so precisely may have no
relationship to what the author intended.
John Sowa