Submissions are now closed! Check the accepted papers and the workshop program here.

We invite papers from both areas – NLP4DBpedia and DBpedia4NLP – 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 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 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. 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All papers must represent original and unpublished work that is not currently under review.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 through CEUR-WS.

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 via Easychair.

For details on the LNCS style, see the Springer Author Instructions here. NLP & DBpedia 2015 submissions are not anonymous.

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