[ANN] DBpedia Spotlight - Text Annotation with DBpedia Resources

Hi all,

we are happy to announce a first release of DBpedia Spotlight - Shedding
Light on the Web of Documents.

The amount of data in the Linked Open Data cloud is steadily increasing.
Interlinking text documents with this data enables the Web of Data to be
used as background knowledge within document-oriented applications such as
search and faceted browsing.

DBpedia Spotlight is a tool for annotating mentions of DBpedia resources in
text, providing a solution for linking unstructured information sources to
the Linked Open Data cloud through DBpedia. The DBpedia Spotlight
Architecture is composed by the following modules:
    * Web application, a demonstration client (HTML/Javascript UI) that
allows users to enter/paste text into a Web browser and visualize the
resulting annotated text.
    * Web Service, a RESTful Web API that exposes the functionality of
annotating and/or disambiguating entities in text. The service returns XML,
JSON or RDF.
    * Annotation Java / Scala API, exposing the underlying logic that
performs the annotation/disambiguation.
    * Indexing Java / Scala API, executing the data processing necessary to
enable the annotation/disambiguation algorithms used.

More information about DBpedia Spotlight can be found at:

http://spotlight.dbpedia.org

DBpedia Spotlight is provided under the terms of the Apache License, Version
2.0. Part of the code uses LingPipe under the Royalty Free License. The
source code can be downloaded from:

http://sourceforge.net/projects/dbp-spotlight

The development of DBpedia Spotlight was supported by:

    * Neofonie GmbH, a Berlin-based company offering leading technologies in
the area of Web search, social media and mobile applications (
http://www.neofonie.de/).
    * The European Commission through the project LOD2 – Creating Knowledge
out of Linked Data (http://lod2.eu/).

Lots of thanks to:

    * Andreas Schultz for his help with the SPARQL endpoint.
    * Paul Kreis for his help with evaluations.
    * Robert Isele and Anja Jentzsch for their help in early stages with the
DBpedia extraction framework.

Cheers,
Pablo N. Mendes, Max Jakob, Andrés García-Silva and Chris Bizer.