DBpedia Open Text Extraction Challenge - TextExt
Sebastian Hellmann <[email protected]> Fri, 3 Mar 2017 15:10:11 +0100
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*DBpedia Open Text Extraction Challenge - TextExt*
Website: http://wiki.dbpedia.org/textext
*_Disclaimer: The call is under constant development, please refer to
the news section. We also acknowledge the initial engineering effort and
will be lenient on technical requirements for the first submissions and
will focus evaluation on the extracted triples and allow late
submissions, if they are coordinated with us_*.
Background
DBpedia and Wikidata currently focus primarily on representing factual
knowledge as contained in Wikipedia infoboxes. A vast amount of
information, however, is contained in the unstructured Wikipedia article
texts. With the DBpedia Open Text Extraction Challenge, we aim to spur
knowledge extraction from Wikipedia article texts in order to
dramatically broaden and deepen the amount of structured
DBpedia/Wikipedia data and provide a platform for benchmarking various
extraction tools.
Mission
Wikipedia has become the ubiquitous source of knowledge for the world
enabling humans to lookup definitions, quickly become familiar with new
topics, read up background infos for news event and many more - even
settling coffee house arguments via a quick mobile research. The mission
of DBpedia in general is to harvest Wikipedia’s knowledge, refine and
structure it and then disseminate it on the web - in a free and open
manner - for IT users and businesses.
News and next events
Twitter: Follow @dbpedia <https://twitter.com/dbpedia>, Hashtag:
#dbpedianlp <https://twitter.com/search?f=tweets&q=%23dbpedianlp&src=typd>
*
LDK <http://ldk2017.org/> conference joined the challenge (Deadline
March 19th and April 24th)
*
SEMANTiCS <http://2017.semantics.cc/> joined the challenge (Deadline
June 11th and July 17th)
*
Feb 20th, 2017: Full example added to this website
*
March 1st, 2017: Docker image (beta)
https://github.com/NLP2RDF/DBpediaOpenDBpediaTextExtractionChallenge
Coming soon:
*
beginning of March: full example within the docker image
*
beginning of March: DBpedia full article text and tables (currently
only abstracts) http://downloads.dbpedia.org/2016-10/core-i18n/
Methodology
The DBpedia Open Text Extraction Challenge differs significantly from
other challenges in the language technology and other areas in that it
is not a one time call, but a continuous growing and expanding challenge
with the focus to *sustainably* advance the state of the art and
transcend boundaries in a *systematic* way. The DBpedia Association and
the people behind this challenge are committed to provide the necessary
infrastructure and drive the challenge for an indefinite time as well as
potentially extend the challenge beyond Wikipedia.
We provide the extracted and cleaned full text for all Wikipedia
articles from 9 different languages in regular intervals for download
and as Docker in the machine readable NIF-RDF
<http://persistence.uni-leipzig.org/nlp2rdf/> format (Example for
Barrack Obama in English
<https://github.com/NLP2RDF/DBpediaOpenDBpediaTextExtractionChallenge/blob/master/BO.ttl>).
Challenge participants are asked to wrap their NLP and extraction
engines in Docker images and submit them to us. We will run
participants’ tools in regular intervals in order to extract:
1.
Facts, relations, events, terminology, ontologies as RDF triples
(Triple track)
2.
Useful NLP annotations such as pos-tags, dependencies, co-reference
(Annotation track)
We allow submissions 2 months prior to selected conferences (currently
_http://ldk2017.org/_ and _http://2017.semantics.cc/_ ). Participants
that fulfil the technical requirements and provide a sufficient
description will be able to present at the conference and be included in
the yearly proceedings. *Each conference, the challenge committee will
select a winner among challenge participants, which will receive 1000€. *
Results
Every December, we will publish a summary article and proceedings of
participants’ submissions at _http://ceur-ws.org/_ . The first
proceedings are planned to be published in Dec 2017. We will try to
briefly summarize any intermediate progress online in this section.
Acknowledgements
We would like to thank the Computer Center of Leipzig University to give
us access to their 6TB RAM server Sirius to run all extraction tools.
The project was created with the support of the H2020 EU project HOBBIT
<https://project-hobbit.eu/> (GA-688227) and ALIGNED
<http://aligned-project.eu/> (GA-644055) as well as the BMWi project
Smart Data Web <http://smartdataweb.de/> (GA-01MD15010B).
Challenge Committee
*
Sebastian Hellmann, AKSW, DBpedia Association, KILT Competence
Center, InfAI, Leipzig
*
Sören Auer, Fraunhofer IAIS, University of Bonn
*
Ricardo Usbeck, AKSW, Simba Competence Center, Leipzig University
*
Dimitris Kontokostas, AKSW, DBpedia Association, KILT Competence
Center, InfAI, Leipzig
*
Sandro Coelho, AKSW, DBpedia Association, KILT Competence Center,
InfAI, Leipzig
Contact Email: [email protected]_
<mailto:[email protected]>
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<p><b>DBpedia Open Text Extraction Challenge - TextExt</b></p>
<p>Website: <a href="http://wiki.dbpedia.org/textext">http://wiki.dbpedia.org/textext</a></p>
<p><strong><u>Disclaimer: The call is under constant development,
please refer to the news section. We also acknowledge the
initial
engineering effort and will be lenient on technical
requirements for
the first submissions and will focus evaluation on the
extracted
triples and allow late submissions, if they are coordinated
with us</u></strong>.</p>
<h3 class="western">Background</h3>
<p>DBpedia and Wikidata currently focus primarily on representing
factual knowledge as contained in Wikipedia infoboxes. A vast
amount
of information, however, is contained in the unstructured
Wikipedia
article texts. With the DBpedia Open Text Extraction Challenge, we
aim to spur knowledge extraction from Wikipedia article texts in
order to dramatically broaden and deepen the amount of structured
DBpedia/Wikipedia data and provide a platform for benchmarking
various extraction tools.</p>
<h3 class="western">Mission</h3>
<p>Wikipedia has become the ubiquitous source of knowledge for the
world enabling humans to lookup definitions, quickly become
familiar
with new topics, read up background infos for news event and many
more - even settling coffee house arguments via a quick mobile
research. The mission of DBpedia in general is to harvest
Wikipedia’s
knowledge, refine and structure it and then disseminate it on the
web
- in a free and open manner - for IT users and businesses.</p>
<h3 class="western">News and next events</h3>
<p>Twitter: <a href="https://twitter.com/dbpedia">Follow @dbpedia</a>,
Hashtag: <a
href="https://twitter.com/search?f=tweets&q=%23dbpedianlp&src=typd">#dbpedianlp</a></p>
<ul>
<li>
<p style="margin-bottom: 0cm"><a href="http://ldk2017.org/">LDK</a>
conference joined the challenge (Deadline March 19th and April
24th) </p>
</li>
<li>
<p style="margin-bottom: 0cm"><a
href="http://2017.semantics.cc/">SEMANTiCS</a> joined the
challenge (Deadline June 11th and July 17th) </p>
</li>
<li>
<p style="margin-bottom: 0cm">Feb 20th, 2017: Full example added
to this website </p>
</li>
<li>
<p>March 1st, 2017: Docker image (beta) <a
href="https://github.com/NLP2RDF/DBpediaOpenDBpediaTextExtractionChallenge">https://github.com/NLP2RDF/DBpediaOpenDBpediaTextExtractionChallenge</a>
</p>
</li>
</ul>
<p>Coming soon:</p>
<ul>
<li>
<p style="margin-bottom: 0cm">beginning of March: full example
within the docker image </p>
</li>
<li>
<p>beginning of March: DBpedia full article text and tables
(currently only abstracts) <a
href="http://downloads.dbpedia.org/2016-10/core-i18n/">http://downloads.dbpedia.org/2016-10/core-i18n/</a>
</p>
</li>
</ul>
<h3 class="western">Methodology</h3>
<p>The DBpedia Open Text Extraction Challenge differs significantly
from other challenges in the language technology and other areas
in
that it is not a one time call, but a continuous growing and
expanding challenge with the focus to <strong>sustainably</strong>
advance the state of the art and transcend boundaries in a <strong>systematic</strong>
way. The DBpedia Association and the people behind this challenge
are
committed to provide the necessary infrastructure and drive the
challenge for an indefinite time as well as potentially extend the
challenge beyond Wikipedia.</p>
<p>We provide the extracted and cleaned full text for all Wikipedia
articles from 9 different languages in regular intervals for
download
and as Docker in the machine readable <a
href="http://persistence.uni-leipzig.org/nlp2rdf/">NIF-RDF</a>
format (Example for <a
href="https://github.com/NLP2RDF/DBpediaOpenDBpediaTextExtractionChallenge/blob/master/BO.ttl">Barrack
Obama in English</a>). Challenge participants are asked to wrap
their
NLP and extraction engines in Docker images and submit them to us.
We
will run participants’ tools in regular intervals in order to
extract:</p>
<ol>
<li>
<p>Facts, relations, events, terminology, ontologies as RDF
triples (Triple track)</p>
</li>
<li>
<p>Useful NLP annotations such as pos-tags, dependencies,
co-reference (Annotation track)</p>
</li>
</ol>
<p>We allow submissions 2 months prior to selected conferences
(currently <a href="http://ldk2017.org/"><u>http://ldk2017.org/</u></a>
and <a href="http://2017.semantics.cc/"><u>http://2017.semantics.cc/</u></a>
). Participants that fulfil the technical requirements and provide
a
sufficient description will be able to present at the conference
and
be included in the yearly proceedings. <strong>Each conference,
the
challenge committee will select a winner among challenge
participants, which will receive 1000€. </strong>
</p>
<h3 class="western">Results</h3>
<p>Every December, we will publish a summary article and proceedings
of participants’ submissions at <a href="http://ceur-ws.org/"><u>http://ceur-ws.org/</u></a>
. The first proceedings are planned to be published in Dec 2017.
We
will try to briefly summarize any intermediate progress online in
this section.</p>
<h3 class="western">Acknowledgements</h3>
<p>We would like to thank the Computer Center of Leipzig University
to give us access to their 6TB RAM server Sirius to run all
extraction tools.</p>
<p>The project was created with the support of the H2020 EU project
<a href="https://project-hobbit.eu/">HOBBIT</a> (GA-688227) and
<a href="http://aligned-project.eu/">ALIGNED</a> (GA-644055) as
well
as the BMWi project <a href="http://smartdataweb.de/">Smart Data
Web</a>
(GA-01MD15010B).</p>
<h3 class="western">Challenge Committee</h3>
<ul>
<li>
<p>Sebastian Hellmann, AKSW, DBpedia Association, KILT
Competence Center, InfAI, Leipzig</p>
</li>
<li>
<p>Sören Auer, Fraunhofer IAIS, University of Bonn</p>
</li>
<li>
<p>Ricardo Usbeck, AKSW, Simba Competence Center, Leipzig
University</p>
</li>
<li>
<p>Dimitris Kontokostas, AKSW, DBpedia Association, KILT
Competence Center, InfAI, Leipzig</p>
</li>
<li>
<p>Sandro Coelho, AKSW, DBpedia Association, KILT Competence
Center, InfAI, Leipzig</p>
</li>
</ul>
<p>Contact Email: <a
href="mailto:[email protected]"><u>[email protected]</u></a></p>
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