To: | ontolog-forum@xxxxxxxxxxxxxxxx |
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From: | FERENC KOVACS <f.kovacs@xxxxxxxxxxxxxx> |
Date: | Sun, 7 Feb 2010 08:43:45 +0000 (GMT) |
Message-id: | <818490.43221.qm@xxxxxxxxxxxxxxxxxxxxxxxxxxx> |
David,
So you understand to some degree the several stages of the SDLC (systems development life cycle)
(top)
requirements
analysis
design
coding
implementation
maintenance
(bottom)
To soem extent, yes. here you go
In Translating a text from L1 to L2 (the requirements) the input is not a single word to be translated into another single word as output, but an *indentifierL1* to be translated to identifier of reality chunk(L1L2), which is a domain. This domain must have an inventory of the chunks so identified that can be accessed from L1 , L2, Ln.
The semantic analysis therefore results in content words (grammar words ignored), which are further broken down as 1) headings, titles and labels, 2) messages. Both groups are made up of lists of variable lengths. They are further broken down into semantic primitives that enable sorted list of objects (both names of chunks of reality and verbal (lingustic objects) which are currently kept as separate repositories as dictionaries and lexicons. But to maintain identity between a real object and its name, you need to be familiar with both. If you disregard this connection then may translate phraseL1 into L2 that results in no equivalent (identity) relation with respect to the purpose of the exercise.
In designing a system that makes provisions for such a requirement you do not need such a vast amount of number crunching, but a more appropriate structure of knowledge of both linguistic and lexical information. More importantly you want a better access, which should involve a dynamic aspect of representing how mental operations change such repertories in reality before you chose any method of coding and implementation to avoid maintenance problems later. And as you know it is sometimes cheaper to scrap an unsatisfactory system than patching it ad infinitum. A new system is needed with new paradigms when the old one keeps you frustrated.
The current ontologies focus on objects only, properties are not structured into repositories and relations are now defined in a funny idiosyncretic way that does not allow integration of ontologies. The contained in, or partof relation, etc. too are very trivial and uninteresting from a NL translation point of view.
Statistical processing approach makes no sense in this adventure to me. Neither does a system that does not cater for people with different level (specificity) of knowledge or procedures to maintain the repository updated all the time as new elements emerge.
Ferenc
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