Hello Mitko,
i think it is Curran's test-query and aims all properties, and not
only dbpedia-onto prop's which are defined in the dataset, but anyway
i think we take it only as a test-query to understand how the engine
works, would i say... Baran.
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On Fri, 27 May 2011 09:10:25 +0200, Mitko Iliev <imi...@gmail.com> wrote:
> Hi All,
>
> Why not simply use the dbpedia ontology to get properties?
> something like "?p a DatatypeProperty" etc.
>
> Regards,
> Mitko
>
> On May 27, 2011, at 12:35 AM, baran_H wrote:
>
>> On Thu, 26 May 2011 22:09:02 +0200, Kingsley Idehen
>> <kide...@openlinksw.com> wrote:
>>> On 5/26/11 3:36 PM, baran_H wrote:
>>>>
>>>> LIMIT doesn't simply the Distinct computation. It simply limits the
>>>> resultset size.
>>
>> --------------------------------------------------------------------
>> Dear K. Idehen,
>> i see above baran_H wrote, but i never wrote such a comment, it has
>> nothing to do with my previous posting, also your reply below is
>> for me not a reply to my posting, in my posting i wrote an algorithm,
>> where you can see that for LIMIT 1 DISTINCT should NEVER REQUIRE
>> computation time as you mentioned in your previous posting to
>> the question
>>
>>> Without 'distinct' it does work:
>>> select ?property where {
>>> ?s ?property ?o.
>>> } limit 1
>>>
>>> Why might this be?
>>
>> with: 'Because Distinct requires more work.'
>>
>> If it is 'really' so, than I cannot accept such a brutally
>> irrational thing whatever someone argues instead of saying:
>> 'We will correct it.'
>>
>> Dear K. Idehen, please see my previous posting with my algorithm
>> IF you want to answer my posting directly with correct citing, if
>> not, it doesn't matter, it is not very unusual in this list to have
>> a not answered posting...
>>
>> Thanks, Baran.
>> -------------------------------------------------------------------
>>> LIMIT doesn't *simplify* the Distinct computation per se.. It simply
>>> limits the
>>> resultset size of the query.
>>>
>>> Virtuoso is a Quad Store, so you have duplicate data across Named
>>> Graphs. This is part of the evaluation cost. If you scope your query to
>>> a specific Named Graph it has less to evaluate. Ultimately there's
>>> always overhead. Even in the case of DBpedia, we do have some linksets
>>> placed in their own Named Graphs i.e, distinct from the Graph IRI:
>>> http://dbpedia.org .
>>>
>>
>>
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