* Lars Aronsson <[email protected]> [Mon, 24 Jan 2011 07:06:02 +0100]:
> On 01/22/2011 08:15 PM, Bryan Tong Minh wrote:
> > Having a clear separate input text field "Author: ____" is much more
> > user friendly {{#fileauthor:}}, which is so to say, a type of 
obscure
> > MediaWiki jargon.
>
> I disagree. In real life, there are always more compliated
> cases, where an author is not an author, but two authors
> or a sculptor, or one painter and one photographer. These
> things never fit in a single "author" field, and the same goes
> for any other separated fields. But the free-form Wikipedia
> can handle all real-world cases in plain human language.
>
> Various "expert systems" based on "artificial intelligence"
> existed since the 1980s, but none of them produced a
> universal encyclopedia. Only the text-based Wikipedia did.
> After this humiliating fact, the same AI people (now dressed
> as "semantic web" scholars) come and claim that they too
> could have built Wikipedia, if it only were more structured.
> They are wrong, of course. Lack of structure is precisely
> what built Wikipedia.
>
>
One may have not just a single triple for that, but the list / set of 
triples for the same person in a different role (different kind of 
author). There are two extremes - not to have any structure or to be 
overly structural. If there are few extra fields for an image 
description, why don't generalize it for all kinds of measured data - 
geographical, historical, population statistics, financial and 
economical data and so on? Why only the images are allowed to have 
structural and measurable data? However, I don't think that Wikipedia 
should have AI, because it requires huge computing power, and the 
problem is that AI algorithms are not efficient enough. To have the data 
structured is not a bad thing. It probably should not even try to do 
SPARQL, but offer these things to external sits. Don't make complex 
queries, leave it for offline tools / bots or toolserver. Semantic bots 
are a good idea - they might mine the data finding the cross-sets. It 
should be even lighter than SMW. However, I might be wrong.
Dmitriy

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