Isn't that Wikidata?
--
Paul Houle
paul.ho...@ontology2.com
On Mon, Mar 6, 2017, at 04:28 PM, John Flynn wrote:
> I applaud this initiative to extract triples from Wikipedia open text.
> However, it would be useful to initiate a parallel challenge/effort to
> represent a limited portion of the current Wikipedia article text as
> semantic representation, eliminating the text altogether. In this
> approach, the Wikipedia information would be semantically encoded as
> its original representation, as opposed to using text to represent the
> information. A small subset of Wikipedia subject matter could be used
> for this experiment. After the limited Wikipedia domain of interest
> was fully semantically represented, tools could be developed to
> translate the semantic representation into human readable text. It
> seems over the long run creating the original knowledge as a semantic
> representation, instead of text, would result in a Wikipedia knowledge
> base that upon query by humans could automatically perform the
> necessary translation into text in whichever human language the user
> desired. This concept would also facilitate machine to machine use of
> the Wikipedia knowledge base, which is currently difficult, if not
> impossible, due to the textual nature of the information. You could
> also envision tools that would eventually make it easy for authors to
> source the article information directly in semantic representation.
> The end results would be a DBpedia on steroids and the eventually
> elimination of Wikipedia as the original article text sources would no
> longer be needed.
>
> John Flynn
> http://semanticsimulations.com
>
> *From:* Sebastian Hellmann [mailto:hellm...@informatik.uni-leipzig.de]
> *Sent:* Monday, March 06, 2017 5:56 AM *To:* DBpedia *Subject:* [DBpedia-
> discussion] DBpedia Open Text Extraction Challenge - TextExt
>
>
> *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[1], Hashtag: #dbpedianlp[2]
> · LDK[3] conference joined the challenge (Deadline March 19th
> and April 24th)
> · SEMANTiCS[4] 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[5] format (Example for
> Barrack Obama in English[6]). 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[7] (GA-688227) and ALIGNED[8] (GA-644055) as well as the BMWi
> project Smart Data Web[9] (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: dbpedia-textext-challe...@infai.org
> ----------------------------------------------------------------------
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Links:
1. https://twitter.com/dbpedia
2. https://twitter.com/search?f=tweets&q=%23dbpedianlp&src=typd
3. http://ldk2017.org/
4. http://2017.semantics.cc/
5. http://persistence.uni-leipzig.org/nlp2rdf/
6.
https://github.com/NLP2RDF/DBpediaOpenDBpediaTextExtractionChallenge/blob/master/BO.ttl
7. https://project-hobbit.eu/
8. http://aligned-project.eu/
9. http://smartdataweb.de/
------------------------------------------------------------------------------
Announcing the Oxford Dictionaries API! The API offers world-renowned
dictionary content that is easy and intuitive to access. Sign up for an
account today to start using our lexical data to power your apps and
projects. Get started today and enter our developer competition.
http://sdm.link/oxford
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