We have received quite a few requests for an extended deadline. We understand that working with large amount of data such as DBpedia is difficult and time consuming. The deadline will therefore be extended until Thursday, July 18th, 23:59 Hawaii time. However, we would like to appeal to all authors to submit an abstract, already. We would also be happy, if you submitted as soon as possible.
* new deadline: July 18th, 2013 * please submit abstract now * we are still looking for a sponsor to create a challenge: http://nlp-dbpedia2013.blogs.aksw.org/sponsors
Apologies for multiple posting! ======================= NLP & DBpedia Workshop 2013 ======================= Free, open, interoperable and multilingual NLP for DBpedia and DBpedia for NLP: http://nlp-dbpedia2013.blogs.aksw.org/
Collocated with the International Semantic Web Conference 2013 (ISWC 2013) 21-22 October 2013, in Sydney, Australia (*Submission deadline July 18th*, 23:59 Hawaii time) **********************************
Recently, the DBpedia community has experienced an immense increase in activity and we believe, that the time has come to explore the connection between DBpedia & Natural Language Processing (NLP) in a yet unpreceded depth. The goal of this workshop can be summarized by this (pseudo-) formula:
NLP & DBpedia == DBpedia4NLP && NLP4DBpedia http://db0.aksw.org/downloads/CodeCogsEqn_bold2.gif
DBpedia has a long-standing tradition to provide useful data as well as a commitment to reliable Semantic Web technologies and living best practices. With the rise of WikiData, DBpedia is step-by-step relieved from the tedious extraction of data from Wikipedia's infoboxes and can shift its focus on new challenges such as extracting information from the unstructured article text as well as becoming a testing ground for multilingual NLP methods.
Contribution ========= Within the timeframe of this workshop, we hope to mobilize a community of stakeholders from the Semantic Web area. We envision the workshop to produce the following items: * an open call to the DBpedia data consumer community will generate a wish list of data, which is to be generated from Wikipedia by NLP methods. This wish list will be broken down to tasks and benchmarks and a GOLD standard will be created. * the benchmarks and test data created will be collected and published under an open license for future evaluation (inspired by OAEI and UCI-ML). An overview of the benchmarks can be found here: http://nlp-dbpedia2013.blogs.aksw.org/benchmarks
Please sign up to our mailing list, if you are interested in discussing guidelines and NLP benchmarking: http://lists.informatik.uni-leipzig.de/mailman/listinfo/nlp-dbpedia-public
Important dates =========== 18 July 2013, Paper Submission Deadline 9 August 2013, Notification of accepted papers sent to authors
Motivation ======= The central role of Wikipedia (and therefore DBpedia) for the creation of a Translingual Web has recently been recognized by the Strategic Research Agenda (cf. section 3.4, page 23) and most of the contributions of the recently held Dagstuhl seminar on the Multilingual Semantic Web also stress the role of Wikipedia for Multilingualism. As more and more language-specific chapters of DBpedia appear (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 ).
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 license 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.
NLP4DBpedia ========== DBpedia has been around for quite a while, infusing the Web of Data with multi-domain data of decent quality. These triples are, however, mostly extracted from Wikipedia infoboxes. To unlock the full potential of Wikipedia articles for DBpedia, the information contained in the remaining part of the articles needs to be analysed and triplified. Here, the NLP techniques may be of favour.
DBpedia4NLP ========== On the other hand NLP, and information extraction techniques in particular, involve various resources while processing texts from various domains. These resources may be used e.g. as an element of a solution e.g. gazetteer being an important part of a rule created by an expert or disambiguation resource, or while delivering a solution e.g. within machine learning approaches. DBpedia easily fits in both of these roles.
We invite papers from both these areas including: 1. 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. 2. Representation of NLP tool output and NLP resources as RDF/OWL, and linking the extracted output to the LOD cloud. 3. Novel applications using the extracted knowledge, the Web of Data or NLP DBpedia-based methods.
The specific topics are listed below.
Topics ===== - Improving DBpedia with NLP methods - Finding errors in 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 co-reference resolution - 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 for potential data extracted from Wikipedia articles - 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 Wikipedia page: http://en.wikipedia.org/wiki/Natural_language_processing#Major_tasks_in_NLP 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).
Submission formats ==============
Paper submission ----------------------- 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.
* Full research paper (up to 12 pages) * Position papers (up to 6 pages) * Use case descriptions (up to 6 pages) * Data/benchmark paper (2-6 pages, depending on the size and complexity)
Note: data and benchmarks papers are meant to provide a citable reference for your data and benchmarks. We kindly require, that you upload any data you use to our benchmark repository in parallel to the submission. We recommend to use an open license (e.g. CC-BY), but minimum requirement is free use. Please write to the mailing list, if you have any problems.
Full instructions are available at: http://nlp-dbpedia2013.blogs.aksw.org/submission/
Submission of data and use cases -------------------------------------------- This workshop also targets non-academic users and developers. If you have any (open) data (e.g. texts or annotations) that can be used for benchmarking NLP tools, but do not want or needd to write an academic paper about it, please feel free to just add it to this table: http://tinyurl.com/nlp-benchmarks or upload it to our repository: http://github.com/dbpedia/nlp-dbpedia
Full instructions are available at: http://nlp-dbpedia2013.blogs.aksw.org/benchmarks/
Also if you have any ideas, use cases or data requests please feel free to just post them on our mailing list: nlp-dbpedia-public [at] lists.informatik.uni-leipzig.de or send them directly to the chairs: nlp-dbpedia2013 [at] easychair.org
Program committee ============== * Guadalupe Aguado, Universidad Politécnica de Madrid, Spain * Chris Bizer, Universität Mannheim, Germany * Volha Bryl, Universität Mannheim, Germany * Paul Buitelaar, DERI, National University of Ireland, Galway * Charalampos Bratsas, OKFN, Greece, ???????????? ???????????? ????????????, (Aristotle University of Thessaloniki), Greece * Philipp Cimiano, CITEC, Universität Bielefeld, Germany * Samhaa R. El-Beltagy, ?????_????? (Nile University), Egypt * Daniel Gerber, AKSW, Universität Leipzig, Germany * Jorge Gracia, Universidad Politécnica de Madrid, Spain * Max Jakob, Neofonie GmbH, Germany * Anja Jentzsch, Hasso-Plattner-Institut, Potsdam, Germany * Ali Khalili, AKSW, Universität Leipzig, Germany * Daniel Kinzler, Wikidata, Germany * David Lewis, Trinity College Dublin, Ireland * John McCrae, Universität Bielefeld, Germany * Uroš Miloševic', Institut Mihajlo Pupin, Serbia * Roberto Navigli, Sapienza, Università di Roma, Italy * Axel Ngonga, AKSW, Universität Leipzig, Germany * Asunción Gómez Pérez, Universidad Politécnica de Madrid, Spain * Lydia Pintscher, Wikidata, Germany * Elena Montiel Ponsoda, Universidad Politécnica de Madrid, Spain * Giuseppe Rizzo, Eurecom, France * Harald Sack, Hasso-Plattner-Institut, Potsdam, Germany * Felix Sasaki, Deutsches Forschungszentrum für künstliche Intelligenz, Germany * Mladen Stanojevic', Institut Mihajlo Pupin, Serbia * Hans Uszkoreit, Deutsches Forschungszentrum für künstliche Intelligenz, Germany * Rupert Westenthaler, Salzburg Research, Austria * Feiyu Xu, Deutsches Forschungszentrum für künstliche Intelligenz, Germany
Contact ===== Of course we would prefer that you will post any questions and comments regarding NLP and DBpedia to our public mailing list at: nlp-dbpedia-public [at] lists.informatik.uni-leipzig.de
If you want to contact the chairs of the workshop directly, please write to: nlp-dbpedia2013 [at] easychair.org
Kind regards, Sebastian Hellmann, Agata Filipowska, Caroline Barrière, Pablo N. Mendes, Dimitris Kontokostas