Hi Peter,
On 10/9/24 2:26 PM, Peter F. Patel-Schneider wrote:
I use the QLever Wikidata SPARQL service at
https://qlever.cs.uni-freiburg.de/wikidata/
The Virtuoso service I use is at
https://wikidata.demo.openlinksw.com/sparql
I believe that both of these are the standard endpoints and are the
same that you used.
peter
For this kind of transitive closure Virtuoso needs a starting point.
https://wikidata.demo.openlinksw.com/sparql?default-graph-uri=http%3A%2F%2Fwww.wikidata.org%2F&query=SELECT+%3Fsub+%3Fsuper+WHERE+%7B%0D%0A++%3Fsub+wdt%3AP279%2B+%3Fsuper+.%0D%0A+++FILTER+%28%3Fsub+%3D+%3Chttp%3A%2F%2Fwww.wikidata.org%2Fentity%2FQ391414%3E%29%0D%0A%7D+%0D%0A&format=text%2Fhtml&timeout=30000&signal_void=on
Can you not share a similar SPARQL Protocol link for QLever?
Kingsley
On 10/9/24 14:21, Kingsley Idehen via Wikidata wrote:
Hi Peter,
On 10/9/24 11:26 AM, Peter F. Patel-Schneider wrote:
Here is a query that I wanted to evaluate:
SELECT ?sub ?super WHERE {
?sub wdt:P279+ ?super .
}
Fine on QLever, fails immediately on Virtuoso, times out in Blazegraph.
Please share the Virtuoso SPARQL endpoint URL for this query. That's
enables a common start point. In addition, what's the SPARQL service
endpoint for the QLever instance you are using?
Kingsley
It would be a good idea to collect wanted but difficult queries to
help inform the WDQS team when they finally replace Blazegraph. I
have over 60 queries that I ran during investigations of the
Wikidata ontology. Some of them were too tough for QLever and
quite a few were pieces of the too-tough queries that I then
combined the results of.
peter
On 10/9/24 10:43, Kingsley Idehen via Wikidata wrote:
Denny and others,
Here’s my basic goto query for SPARQL.
|SELECT (SAMPLE(?s) as ?sample) (count(*) as ?count) ?o WHERE {?s a
?o} GROUP BY ?o ORDER BY DESC (?count) LIMIT 20 |
SPARQL Results Links:
1.
Solution from Our Wikidata Endpoint
<https://wikidata.demo.openlinksw.com/sparql?default-graph-uri=http%3A%2F%2Fwww.wikidata.org%2F&query=SELECT+%28SAMPLE%28%3Fs%29+as+%3Fsample%29+%28count%28*%29+as+%3Fcount%29+%3Fo%0D%0AWHERE+%7B%3Fs+a+%3Fo%7D%0D%0AGROUP+BY+%3Fo%0D%0AORDER+BY+DESC+%28%3Fcount%29%0D%0ALIMIT+20&format=text%2Fx-html%2Btr&timeout=30000&signal_void=on>
2.
QLever’s Endpoint doesn’t handling this, assuming
https://qlever.cs.uni-freiburg.de/wikidata/sk8I2D is the
correct one.
What am I missing here?
Kingsley
On 10/9/24 10:31 AM, Kingsley Idehen via Wikidata wrote:
HI Denny,
On 10/2/24 5:05 AM, Denny Vrandečić wrote:
The most promising show of "we are ready" for the Virtuoso Open
Source edition would be what QLever has been doing for a while:
to provide a public endpoint with the data loaded, and kept up to
date using the public edit stream. That would be an undeniably
strong argument for "just use this!"
Aren't you aware of the public endpoints we've provided for years?
[1] https://wikidata.demo.openlinksw.com/sparql
[2] https://wikidata.demo.openlinksw.com/fct
That's VOS based.
Is there something that's missing etc?
Kingsley
On Thu, Sep 26, 2024 at 4:32 PM Samuel Klein <[email protected]>
wrote:
An updated benchmark eval (or self-evals) for the top db
candidates
seems called for :) we would all love to see it.
Ideally with a canonical hardware or vm spec that all can use...
I don't know if the QLever self-eval from the spring is the
right place
to start, but I believe these
<https://ad-research.cs.uni-freiburg.de/benchmarks/wdqs-queries/>
are
the ~300 queries they used for a Wikidata benchmark.
🌍🌏🌎🌑
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Regards,
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OpenLink Software
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Weblogs (Blogs):
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Data Access Drivers
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--
Regards,
Kingsley Idehen
Founder & CEO
OpenLink Software
Home Page: http://www.openlinksw.com
Community Support: https://community.openlinksw.com
Weblogs (Blogs):
Company Blog: https://medium.com/openlink-software-blog
Virtuoso Blog: https://medium.com/virtuoso-blog
Data Access Drivers Blog:
https://medium.com/openlink-odbc-jdbc-ado-net-data-access-drivers
Personal Weblogs (Blogs):
Medium Blog: https://medium.com/@kidehen
Legacy Blogs: http://www.openlinksw.com/blog/~kidehen/
http://kidehen.blogspot.com
Profile Pages:
Pinterest: https://www.pinterest.com/kidehen/
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