|To:||"ONTAC-WG General Discussion" <ontac-forum@xxxxxxxxxxxxxx>|
|From:||"Obrst, Leo J." <lobrst@xxxxxxxxx>|
|Date:||Fri, 7 Oct 2005 17:13:32 -0400|
I'll weigh in to support Pat on a couple of these points. I apologize in advance if I get too technical.
The whole point of using logic for ontologies and for expressing natural language semantics is to use a formal language in which the meanings of ambiguous natural language statements can be stated unambiguously, i.e., teasing out those distinct elements of ambiguity and representing them and showing the dimensions of ambiguity. If I say "the tank next to the bank", there are at least 4 possible interpretations/meanings: 1) the military vehicle next to the river bank, 2) the military vehicle next to the financial bank building, 3) the liquid container next to the river bank, 4) the liquid container next to the financial bank building. With additional natural language, as in 1-4, we can tease out the ambiguities, but using logic we can formally represent those distinctions in a formal language that machines can use.
We use human language terms to label ontology concepts because those terms are typically readily available to us human beings in that language (English, Chinese, etc.) and we tend to largely intuitively agree on their meaning. And terms and concepts are quite distinct items: terms are labels that index the concepts which express and model the meaning of those labels.
So the use of these labeling terms is really to aid humans who look over the ontology concepts (represented formally in an ontology), and say, yes, this label "Person" for the concept Person with these formally represented relations, properties, superclasses, subclasses, and axioms is really what I mean by the English word "person", or is at least an approximation of what I mean. I.e., a person is necessarily all those things but may in addition be other things, that is, we try to initially capture the "necessary" conditions and over time capture other "sufficient" conditions. Humans necesarily are mammals and have parents, but only sometimes like to chew gum or sometimes do not have addresses. If you don't have an address, you still are human.
Most semanticists in natural language use what's called "model-theoretic semantics" to express the set of formal models which are licensed by the logical statements/expressions: i.e., you go from the axioms to the formal models in ontological engineering just like you go from the natural language sentences (of English, Chinese, etc..) as expressed in logical statements to their formal models (typically represented mathematically in set theory or structures using set theory).
Why? Because this syntax-to-semantic (axioms to models) mapping enables you to characterize what you "really mean" and compare that to what you "intend to mean." Example: you might have axioms about parent and children classes in an ontology, i.e., parent is a role of a person (one can be both a parent and a child, an employee, a carpenter, an author, stamp collector, etc.), but forgot to include an axiom which states that no parent can be his/her own parent, nor can be his/her own child.
You may not see this lapse in your ontology axioms, but on looking at the formal models licensed by those axioms, you will see these unintended models (this is Mike Gruninger's point, I think), i.e., unless you axiomatize explicitly against a parent being his/her own parent, you will get formal models in which John is his own parent and his own child -- NOT what you intend, I think, if you really want to capture the real world relationships.
So axioms and models (syntax and semantics) help us to gauge what we really are modeling when we create an ontology which tries to model the real world. Other less formal languages (without a logic behind them) such as XML, UML, etc., cannot help us.
Additionally one point is that humans tend to use language in a way that helps us to label and then link the important concepts and combinations of concepts that are necessary for us to communicate to other humans. So you will probably as a human have a concept correlated to the term "person" but maybe not a direct concept correlated to the phrase (terms in a syntactically correct sequence) "a person who eats broccoli while reading the newspaper". That phrase is indeed expressible using natural language and links concepts like "person", "someone who eats broccoli", and "someone who reads the newspaper", but you don't need a single concept for that, just a composition of concepts.
Finally, ontology precedes epistemology (not to get into philosophical arguments!): you can only ground belief on knowledge, i.e., evidence on what you do know. You may not know which of 3 birth dates a prospective terrorist has (you have evidence for all 3), but you do know that all humans have only one birth date.
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