[open-linguistics] CfP: 3rd International Workshop on NLP & DBpedia 2015
Erp, M.G.J. van
marieke.van.erp at vu.nl
Fri May 29 12:53:00 UTC 2015
*apologies for cross-posting*
NLP & DBpedia 2015 - First Call for Papers
3rd International Workshop on NLP & DBpedia 2015
October 11th or 12th, 2014
Bethlehem, PA, USA
Collocated with the 14th International Semantic Web Conference (ISWC2015).
Submission Deadline: July 1st, 2015
Notification of Acceptance: July 31st, 2015
Workshop URI: https://nlpdbpedia2015.wordpress.com/
Submissions via: https://easychair.org/conferences/?conf=nlpdbpedia2015
Contact: nlpdbpedia2015 at easychair.org
The central role of Wikipedia (and therefore DBpedia) for the creation
of a Translingual Web has been recognized by the Strategic Research
Agenda (cf. section 3.4, page 23) and most of the contributions of the
Dagstuhl seminar on the Multilingual Semantic Web also stress the role
of Wikipedia for Multilingualism. The previous editions of the
NLP&DBpedia workshop also contribute to this understanding.
As more and more language-specific chapters of DBpedia are created
(currently 14 language editions), DBpedia is becoming a driving factor
for a Linguistic Linked Open Data cloud as well as localized LOD clouds
with specialized domains (e.g. the Dutch windmill domain ontology
created from http://nl.dbpedia.org or Japanese domain ontology of screws
The data contained in Wikipedia and DBpedia have ideal properties for
making them a controlled testbed for NLP. Wikipedia and DBpedia are
multilingual and multi-domain, the communities maintaining these
resource are very open and it is easy to join and contribute. The open
licence allows data consumers to benefit from the content and many parts
are collaboratively editable. Especially, the data in DBpedia is widely
used and disseminated throughout the Semantic Web.
With the foundation of the DBpedia Association and the frequent releases
of the DBpedia+ Data Stack, this workshop hopes to channel contributions
of the NLP research community into the data ecosystem of DBpedia and
LOD, thus easing the use of interlinked language resources as well as
increasing the performance of knowledge-based NLP approaches.
We envision the workshop to produce the following items:
* an open call to the DBpedia data consumer community that will generate
a wish list of data, which is to be generated from Wikipedia using NLP
methods (for certain domains and application scenarios). This wish list
will be broken down to tasks and benchmarks and as a result GOLD
standard will be created.
* the benchmarks and test data created will be collected and published
under an open licence for future evaluation (inspired by
* strengthen the link between DBpedia and NLP communities that currently
meet two times a year at DBpedia developers workshops.
We also offer all authors the chance to contribute their data to the
regular DBpedia releases in April and October.
DBpedia has been around for quite a while, infusing the Web of Data with
multi-domain data of decent quality. The data in DBpedia is, however,
mostly extracted from Wikipedia infoboxes, while the remaining parts of
Wikipedia are to a large extent not exploited for DBpedia. Here, NLP
techniques may help improving DBpedia.
Extracting additional triples from the plain text information in
Wikipedia, either unsupervised or using the existing triples as training
information, could multiply the information in DBpedia, or help telling
correct from incorrect information by finding supporting text passages.
Furthermore, analyzing the semantics of other structures in Wikipedia,
such as tables, lists, or categories, would help make DBpedia richer.
Finally, since Wikipedia exists in more than 200 languages, we are
particularly interested in seeing NLP approaches not only working for
English, but also for other languages, in order to leverage the huge
amount of knowledge captured in the different language editions.
NLP approaches enable also improving quality of DBpedia, especially by
extracting content from sources other than Wikipedia that may validate
the data in DBpedia.
On the other hand, NLP and information extraction techniques often
involve various resources while processing texts from different domains.
As high-quality annotated data is often too expensive and time-consuming
to obtain, NLP researchers are increasingly looking to the Semantic Web
for external structured sources to complement their datasets. Such
resources can be gazetteers to aid a named entity recognition system or
examples of relations between entities to bootstrap a relation finder.
DBpedia can easily be utilised to assist NLP modules in a variety of tasks.
We invite papers from both these areas including:
* Knowledge extraction from text and HTML documents (especially
unstructured and semi-structured documents) on the Web, using
information in the Linked Open Data (LOD) cloud, and especially in DBpedia.
* Representation of NLP tool output and NLP resources as RDF/OWL, and
linking the extracted output to the LOD cloud or the Linguistic LOD cloud .
* Novel applications using the extracted knowledge, the Web of Data or
NLP DBpedia-based methods.
Topics include, but are not limited to
* Enhancing DBpedia with NLP methods
* Finding errors in DBpedia with NLP methods
* Enriching DBpedia with NLP methods
* Improving quality of DBpedia with NLP methods
* Annotation methods for Wikipedia articles
* Cross-lingual data and text mining on Wikipedia
* Pattern and semantic analysis of natural language, reading the Web,
learning by reading
* Large-scale information extraction
* Entity resolution and automatic discovery of Named Entities
* Multilingual entity recognition task of real world entities
* Frequent pattern analysis of entities
* Relationship extraction, slot filling
* Entity linking, Named Entity disambiguation, cross-document
* Disambiguation through knowledge base
* Ontology representation of natural language text
* Analysis of ontology models for natural language text
* Learning and refinement of ontologies
* Natural language taxonomies modeled to Semantic Web ontologies
* Use cases of entity recognition for Linked Data applications
* Impact of entity linking on information retrieval, semantic search
Furthermore, an informal list of NLP tasks can be found on this
These are relevant for the workshop as long as they fit into the
DBpedia4NLP and NLP4DBpedia frame (i.e. the used data evolves around
Wikipedia and DBpedia).
All papers must represent original and unpublished work that is not
currently under review. Papers will be evaluated according to their
significance, originality, technical content, style, clarity, and
relevance to the workshop. At least one author of each accepted paper is
expected to attend the workshop. Accepted papers will be published
We welcome the following types of contributions:
* Full research papers (up to 12 pages).
* Position papers (up to 6 pages)
* Use case descriptions (up to 6 pages)
* Data/benchmark papers (2-6 pages, depending on the size and complexity)
All submissions must be written in English and must be formatted
according to the style for Lecture Notes in Computer Science (LNCS)
Authors. Please submit your contributions electronically in PDF format
For details on the LNCS style, see the Springer Author Instructions at
http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0. NLP &
DBpedia 2015 submissions are not anonymous.
- submission date: July 1st, 2015, 23:59 Hawaii time
- author notifications: July 31st, 2015, 23:59 Hawaii time
- camera-ready: August 21st, 2015, 23:59 Hawaii time
- NLP & DBpedia 2015: October 11th or 12th, 2015
* Heiko Paulheim, University of Mannheim, Germany
* Marieke van Erp, VU Amsterdam, The Netherlands
* Agata Filipowska, Poznan University of Economics, Poland and I2G,
* Pablo N. Mendes, IBM Research, USA
* Martin Brümmer, AKSW, University of Leipzig, Germany
Christian Bizer, University of Mannheim
Volha Bryl, University of Mannheim
Paul Buitelaar, Insight - National University of Ireland, Galway
Philipp Cimiano, University of Bielefeld
Samhaa El-Beltagy, Cairo University
Jorge Gracia, Ontology Engineering Group. Universidad Politécnica de Madrid
Anja Jentzsch, Hasso Plattner Institut
John P. Mccrae, Cognitive Interaction Technology, Center of Excellence
Andrea Moro, Sapienza, Università di Roma
Giuseppe Rizzo, EURECOM
Harald Sack, Hasso-Plattner-Institute for IT Systems Engineering,
University of Potsdam
Felix Sasaki, W3C
Ricardo Usbeck, University of Leipzig
Sebastian Walter, CITEC, Bielefeld University
Krzysztof Wecel, Poznan University of Economics
Rupert Westenthaler, Salzburg Research
Computational Lexicology & Terminology Lab (CLTL)
The Network Institute, VU University Amsterdam
De Boelelaan 1105
1081 HV Amsterdam, The Netherlands
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