An Open Platform for a Large, Multilingual, Semantic Knowledge Graph
The DBpedia project is aiming to extract structured content from the information created in various Wikimedia projects. This structured information resembles an open knowledge graph (KG) which is available for everyone on the Web. A knowledge graph is a special kind of database which stores knowledge in a machine-readable form and provides a means for information to be collected, organised, shared, searched and utilised. Google uses a similar approach to create those knowledge cards during search.
DBpedia currently describes 38.3 million “things” of 685 different “types” in 125 languages, with over 3 billion “facts” (September 2014). It is interlinked to many other databases (e.g., Wikidata, New York Times, CIA World Factbook). The knowledge in DBpedia is exposed through a set of technologies called Linked Data. Started in 2006, DBpedia is one of the first (if not THE first) open knowledge graph on the Web. DBpedia provides tools that allow you to create, maintain, improve, integrate and use KGs to build applications, e.g. BBC has created the World Cup 2010 website by interconnecting textual content and facts from their knowledge base. Data provided by DBpedia was greatly involved in creating this knowledge graph. More recently, IBM's Watson used DBpedia data to win the Jeopardy challenge. Several other large, medium and small companies use data from DBpedia everyday.
DBpedia data is served as Linked Data, which is revolutionizing the way applications interact with the Web. One can navigate this Web of facts with standard Web browsers, automated crawlers or pose complex queries with SQL-like query languages (e.g. SPARQL). Have you thought of asking the Web about all cities with low criminality, warm weather and open jobs? That's the kind of query we are talking about.
We are regularly growing our community through GSoC and can deliver more and more opportunities to you.
DBpedia 2018 Projects
A Neural QA Model for DBpediaExtending Neural SPARQL Machines (NSpM) to cover more DBpedia classes to enable high quality Question Answering
Complex Embeddings for OOV EntitiesThe aim of this project is to enhance the DBpedia Knowledge Base by enabling the model to learn from the corpus and generate embeddings for different...
Web application to detect incorrect mappings across DBpedias in different languagesThe DBpedia mappings for each language are not aligned, causing inconsistencies in the quality of the RDF generated. This is often a consequence of...