Category Archives: User interfaces

DBpedia Entity – Standard Test Collection for Entity Search over DBpedia

Today we are featuring DBpedia Entity, in our blog series of introducting interesting DBpedia applications and tools to the DBpedia community and beyond. Read on and enjoy.

DBpedia-Entity is a standard test collection for entity search over the DBpedia knowledge base. It is meant for evaluating retrieval systems that return a ranked list of entities (DBpedia URIs) in response to a free text user query.

The first version of the collection (DBpedia-Entity v1) was released in 2013, based on DBpedia v3.7 [1]. It was created by assembling search queries from a number of entity-oriented benchmarking campaigns and mapping relevant results to DBpedia. An updated version of the collection, DBpedia-Entity v2, has been released in 2017, as a result of a collaborative effort between the IAI group of the University of Stavanger, the Norwegian University of Science and Technology, Wayne State University, and Carnegie Mellon University [2]. It has been published at the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR’17), where it received a Best Short Paper Honorable Mention Award. See the paper and poster.

DBpedia Entity was published on and is one of many other projects and applications featuring DBpedia.

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Call for Ideas and Mentors for GSoC 2014 DBpedia + Spotlight joint proposal (please contribute within the next days)

We started to draft a document for submission at Google Summer of Code 2014:

We are still in need of ideas and mentors.  If you have any improvements on DBpedia or DBpedia Spotlight that you would like to have done, please submit it in the ideas section now. Note that accepted GSoC students will receive about 5000 USD for a three months, which can help you to estimate the effort and size of proposed ideas. It is also ok to extend/amend existing ideas (as long as you don’t hi-jack them). Please edit here:

Becoming a mentor is also a very good way to get involved with DBpedia. As a mentor you will also be able to vote on proposals, after Google accepts our project. Note that it is also ok, if you are a researcher and have a suitable student to submit an idea and become mentor. After acceptance by Google the student then has to apply for the idea and get accepted.

Please take some time this week to add your ideas and apply as a mentor, if applicable. Feel free to improve the introduction as well and comment on the rest of the document.

Information on GSoC in general can be found here:

Thank you for your help,
Sebastian and Dimitris

Invitation to contribute to DBpedia by improving the infobox mappings + New Scala-based Extraction Framework

Hi all,

in order to extract high quality data from Wikipedia, the DBpedia extraction framework relies on infobox to ontology mappings which define how Wikipedia infobox templates are mapped to classes of the DBpedia ontology.

Up to now, these mappings were defined only by the DBpedia team and as Wikipedia is huge and contains lots of different infobox templates, we were only able to define mappings for a small subset of all Wikipedia infoboxes and also only managed to map a subset of the properties of these infoboxes.

In order to enable the DBpedia user community to contribute to improving the coverage and the quality of the mappings, we have set up a public wiki at which contains:

1.  all mappings that are currently used by the DBpedia extraction framework
2. the definition of the DBpedia ontology and
3. documentation for the DBpedia mapping language as well as step-by-step guides on how to extend and refine mappings and the ontology.

So if you are using DBpedia data and you you were always annoyed that DBpedia did not properly cover the infobox template that is most important to you, you are highly invited to extend the mappings and the ontology in the wiki. Your edits will be used for the next DBpedia release expected to be published in the first week of April.

The process of contributing to the ontology and the mappings is as follows:

1.  You familiarize yourself with the DBpedia mapping language by reading the documentation in the wiki.
2.  In order to prevent random SPAM, the wiki is read-only and new editors need to be confirmed by a member of the DBpedia team (currently Anja Jentzsch does the clearing). Therefore, please create an account in the wiki for yourself. After this, Anja will give you editing rights and you can edit the mappings as well as the ontology.
3. For contributing to the next DBpedia relase, you can edit until Sunday, March 21. After this, we will check the mappings and the ontology definition in the Wiki for consistency and then use both for the next DBpedia release.

So, we are starting kind of a social experiment on if the DBpedia user community is willing to contribute to the improvement of DBpedia and on how the DBpedia ontology develops through community contributions J

Please excuse, that it is currently still rather cumbersome to edit the mappings and the ontology. We are currently working on a visual editor for the mappings as well as a validation service, which will check edits to the mappings and test the new mappings against example pages from Wikipedia. We hope that we will be able to deploy these tools in the next two months, but still wanted to release the wiki as early as possible in order to already allow community contributions to the DBpedia 3.5 release.

If you have questions about the wiki and the mapping language, please ask them on the DBpedia mailing list where Anja and Robert will answer them.

What else is happening around DBpedia?

In order to speed up the data extraction process and to lay a solid foundation for the DBpedia Live extraction, we have ported the DBpedia extraction framework from PHP to Scala/Java. The new framework extracts exactly the same types of data from Wikipedia as the old framework, but processes a single page now in 13 milliseconds instead of the 200 milliseconds. In addition, the new framework can extract data from tables within articles and can handle multiple infobox templates per article. The new framework is available under GPL license in the DBpedia SVN and is documented at

The whole DBpedia team is very thankful to two companies which enabled us to do all this by sponsoring the DBpedia project:

1. Vulcan Inc. as part of its Project Halo ( Vulcan Inc. creates and advances a variety of world-class endeavors and high impact initiatives that change and improve the way we live, learn, do business (
2.  Neofonie GmbH, a Berlin-based company offering leading technologies in the area of Web search, social media and mobile applications (

Thank you a lot for your support!

I personally would also like to thank:

1.  Anja Jentzsch, Robert Isele, and Christopher Sahnwaldt for all their great work on implementing the new extraction framework and for setting up the mapping wiki.
2.  Andreas Lange and Sidney Bofah for correcting and extending the mappings in the Wiki.


Chris Bizer

German government proclaims Faceted Wikipedia/DBpedia Search one of the 365 most innovative ideas in Germany

The German federal government has proclaimed Faceted Wikipedia Search as one of the 365 most innovative ideas in Germany in the context of the Deutschland – Land der Ideen competition. The competition showcases innovative ideas in areas such as science and technology, business, education, art and ecology. The patron of the competition is the German President Horst Köhler.

Faceted Wikipedia/DBpedia Search allows users to ask complex queries, like “Which Rivers flow into the Rhine and are longer than 50 kilometers?” or “Which Skyscrapers in China have more than 50 floors and have been constructed before the year 2000?” against Wikipedia. The answers to these queries are not generated using key word matching as the answers of search engines like Google or Yahoo, but are generated based on structured information that has been extracted from many different Wikipedia articles. Faceted Wikipedia/DBpedia Search allows users to query Wikipedia like a structured database and thus enables them to truly exploit Wikipedia’s collective intelligence.

Faceted Wikipedia/Dbpedia Search can be tested online at

Please click on the example queries below to see Faceted Wikipedia Search in action:

Faceted Wikipedia/DBpedia Search has been jointly developed by neofonie GmbH, Berlin and the Web-based Systems Group at Freie Universität Berlin. Technically, Faceted Wikipedia/DBpedia Search is based on the DBpedia data extraction framework and neofonie search technology.


The DBpedia data extraction framework extracts structured data from Wikipedia, such as the content of infoboxes which summarize relevant facts as a table on the top right-hand side of Wikipedia articles. The extracted data is represented using the Resource Description Framework, a data model for web-based systems. Currently, the framework extracts around 190 million facts from the English editon of Wikipedia and 289 million facts from Wikipedia editions in 90 further languages. The DBpedia data extraction framework is developed by the Web-based Systems group at Freie Universität Berlin and the Agile Knowledge Engineering and Semantic Web group at Universität Leizpig.


The neofonie search engine, neofonie search, is employed to execute complex queries over the extracted data. neofonie search aggregates RDF data from DBpedia with full-text data from Wikipedia. The aggregated data is then divided into hierarchical facets, composed of 200 types with 2.9 million values. In addition to providing the search technology and processing power, neofonie is also responsible for the hosting of the Faceted Wikipedia/DBpedia Search on the Amazon Elastic Compute Cloud (Amazon EC2).

As DBpedia covers a wide range of domains and has a high degree of conceptual overlap with various other open-license datasets, an increasing number of data publishers have started to set data-level links from their data sources to DBpedia, making DBpedia one of the cristalization points of the emerging Web of Linked Data. In the future, the links between databases will allow applications like Faceted Wikipedia Search to answer queries based not only on Wikipedia knowledge but based on knowledge from a world wide web of databases.

Faceted Wikipedia Search will be presented as part of the Land der Ideen series on April 12th, 2010 at neofonie, Berlin.

Additional information about the Land der Ideen competition, DBpedia, neofonie and the Web of Data is found at:

DBpedia Faceted Browser and DBpedia User Script released

We are pleased to announce the release of the DBpedia Faceted Browser by Jona Christopher Sahnwaldt as well as the DBpedia User Script by Anja Jentzsch.

The DBpedia Faceted Browser allows you to explore Wikipedia via a faceted browsing interface. It supports keyword queries and offers relevant facets to narrow down search results, based on the DBpedia Ontology. In this manner, queries such as “recent films about Buenos Aires” can be easily and intuitively posed against DBpedia.
The DBpedia Faceted browser was developed in cooperation with the search engine company Neofonie, which also kindly provided the funding for this project.

The DBpedia User Script is a Greasemonkey script that enhances Wikipedia pages with a link to their corresponding DBpedia page and can be used within Firefox, Safari and Opera with a suitable Greasemonkey plugin.


DBpedia Mobile won the 2nd prize of the Semantic Web Challenge 2008

We are happy to announce that DBpedia Mobile has won the 2nd prize of the Semantic Web Challenge at the 7th International Semantic Web Conference.

DBpedia Mobile is a location-aware client for the Semantic Web that can be used on an iPhone and other mobile devices. Based on the current GPS position of a mobile device, DBpedia Mobile renders a map indicating nearby locations from the DBpedia dataset. Starting from this map, the user can explore background information about his surroundings by navigating along data links into otherWeb data sources. DBpedia Mobile has been designed for the use case of a tourist exploring a city. As the application is not restricted to a xed set of data sources but can retrieve and display data from arbitrary Web data sources, DBpedia Mobile can also be employed within other use cases, including ones unforeseen by its developers. Besides accessing Web data, DBpedia Mobile also enables users to publish their current location, pictures and reviews to the Semantic Web so that they can be used by other Semantic Web applications. Instead of simply being tagged with geographical coordinates, published content is interlinked with a nearby DBpedia resource and thus contributes to the overall richness of the Geospatial Semantic Web.

For more information about DBpedia Mobile please refer to:

DBpedia Mobile released.

Freie Universität Berlin has released DBpedia Mobile.  Based on the current GPS position of a mobile device, DBpedia Mobile renders a map containing information about nearby locations from the DBpedia dataset (currently around 300,000 locations). DBpedia Mobile uses the Marbles Linked Data Browser to render Fresnel-based views for selected resources, as well as its SPARQL capabilities to build the map view. Starting from the map, users can explore background information about locations and can navigate into DBpedia and other interlinked datasets such as GeoNames, Revyu, EuroStat and Flickr.

More information about DBpedia Mobile is found on the project website.