This is probably a dumb question, but I'm going to ask it anyway. ;-)
Is there somewhere place we can find some simple documentation about how to build queries?
And what do we do if we get unexpected
results?
For example, I'm trying out an example query, using the query builder at
http://wikipedia.aksw.org/index.php? (which I found under
the "OnlineAccess" page on
dbpedia.org, and which I'm assuming is an
interface to the new
DBpedia.org data, but please correct me if
that's wrong), to find suburbs less than 10 kms from the CBD, using the following
query:
Subject Predicate Object
?suburb rdf:type Category:Suburbs_of_Sydney
?suburb location <10
But that doesn't find any matches, which I'm guessing is because it seems to be
based on Infoboxes ... so rephrased as an infobox
query, from looking at the other examples I'm guessing it is something like this:
Subject Predicate Object
?Australian Place type suburb
?Australian Place city Sydney
?Australian Place dist1 <10
However, that finds no matches ... but if we increase the distance to 200 kms, like so:
Subject Predicate Object
?Australian Place type suburb
?Australian Place city Sydney
?Australian Place dist1 <200
(saved as:
http://wikipedia.aksw.org/index.php?qid=145 ) ... then it finds 7 matches,
which is good because it means the query
probably made sense, but it should find many more. For example, why doesn't it match
this page:
http://en.wikipedia.org/w/index.php?title=Leichhardt%2C_New_South_Wales&… ,
which contains:
-----------
{{Infobox Australian Place | type = suburb
| name = Leichhardt
| city = Sydney
...
| dist1 = 5
...
}}
-----------
... which was added some time in March - is the answer that the data on
http://wikipedia.aksw.org is old? Or am I just phrasing the
query incorrectly? Or should I be using some other site or tool to perform these queries
on DBpedia?
Also I tried it at
http://dbpedia.org/sparql , with the query below (which was just a wild
guess at the syntax, as the 2204-page
virtdocs.pdf seemed a bit overwhelming, but it's probably wrong), but it kept giving
503 Service unavailable errors:
-----------
select distinct ?Australian Place where type = 'suburb' and city =
'Sydney';
-----------
-- All the best,
Nick.
-----Original Message-----
From: wikitech-l-bounces(a)lists.wikimedia.org
[mailto:wikitech-l-bounces@lists.wikimedia.org]On Behalf Of Chris Bizer
Sent: Thursday, 6 September 2007 2:15 AM
To: wikitech-l(a)lists.wikimedia.org
Subject: [Wikitech-l] DBpedia - Querying Wikipedia like a Database:
Improveddataset released.
Hi all,
after quite some work into improving the DBpedia information
extraction framework, we have released a new version of the DBpedia
dataset today.
DBpedia is a community effort to extract structured information from
Wikipedia and to make this information available on the Web. DBpedia
allows you to ask sophisticated queries against Wikipedia and to link
other datasets on the Web to Wikipedia data.
The DBpedia dataset describes 1,950,000 "things", including at least
80,000 persons, 70,000 places, 35,000 music albums, 12,000 films. It
contains 657,000 links to images, 1,600,000 links to relevant external
web pages and 440,000 external links into other RDF datasets.
Altogether, the DBpedia dataset consists of around 103 million RDF
triples.
The Dataset has been extracted from the July 2007 Wikipedia dumps of
English, German, French, Spanish, Italian, Portuguese, Polish,
Swedish, Dutch, Japanese, Chinese, Russian, Finnish and Norwegian
versions of Wikipedia. It contains descriptions in all these
languages.
Compared to the last version, we did the following:
1. Improved the Data Quality
We increased the quality of the data, be improving the DBpedia
information extraction algorithms. So if you have decided that the old
version of the dataset was too dirty for your application, please look
again, you will be surprised :-)
2. Third Classification Schema Added
We have added a third classification schema to the dataset. Beside of
the Wikipedia categorization and the YAGO classification, concepts are
now also classified by associating them to WordNet synsets.
3. Geo-Coordinates
The dataset contains geo-coordinates for for geographic locations.
Geo-coordinates are expressed using the W3C Basic Geo Vocabulary. This
enables location-based SPARQL queries.
4. RDF Links to other Open Datasets
We interlinked DBpedia with further open datasets and ontologies. The
dataset now contains 440 000 external RDF links into the Geonames,
Musicbrainz, WordNet, World Factbook, EuroStat, Book Mashup, DBLP
Bibliography and Project Gutenberg datasets. Altogether, the network
of interlinked datasources around DBpedia currently amounts to around
2 billion RDF triples which are accessible as Linked Data on the Web.
The DBpedia dataset is licensed under the terms GNU Free Documentation
License. The dataset can be accessed online via a SPARQL endpoint and
as Linked Data. It can also be downloaded in the form of RDF dumps.
Please refer to the DBpedia webpage for more information about the
dataset and its use cases:
http://dbpedia.org/
Many thanks for their excellent work to:
1. Georgi Kobilarov (Freie Universität Berlin) who redesigned and
improved the extraction framework and implemented many of the
interlinking algorithms.
2. Piet Hensel (Freie Universität Berlin) who improved the infobox
extraction code, wrote the unit test suite.
3. Richard Cyganiak (Freie Universität Berlin) for his advice on
redesigning the architecture of the extraction framework and for
helping to solve many annoying Unicode and URI problems.
4. Zdravko Tashev (OpenLink Software) for his patience to try several
times to import buggy versions of the dataset into Virtuoso.
5. OpenLink Software altogether for providing the server that hosts
the DBpedia SPARQL endpoint.
6. Sören Auer, Jens Lehmann and Jörg Schüppel (Universität Leipzig)
for the original version of the infobox extraction code.
7. Tom Heath and Peter Coetzee (Open University) for the RDFS version
of the YAGO class hirarchy.
8. Fabian M. Suchanek, Gjergji Kasneci (Max-Plank-Institut
Saarbrücken) for allowing us to integrate the YAGO classification.
9. Christian Becker (Freie Universität Berlin) for writing the
geo-coordinates and the homepage extractor.
10. Ivan Herman, Tim Berners-Lee, Rich Knopman and many others for
their bug reports.
Have fun exploring the new dataset :-)
Cheers
Chris
--
Chris Bizer
Freie Universität Berlin
Phone: +49 30 838 54057
Mail: chris(a)bizer.de
Web:
www.bizer.de
--
Chris Bizer
Freie Universität Berlin
Phone: +49 30 838 54057
Mail: chris(a)bizer.de
Web:
www.bizer.de
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