Introduction

DBpedia Spotlight is a tool for automatically annotating mentions of DBpedia resources in text, providing a solution for linking unstructured information sources to the Linked Open Data cloud through DBpedia. DBpedia Spotlight recognizes that names of concepts or entities have been mentioned (e.g. "Michael Jordan"), and subsequently matches these names to unique identifiers (e.g. dbpedia:Michael_I._Jordan, the machine learning professor or dbpedia:Michael_Jordan the basketball player). It can also be used for building your solution for Named Entity Recognition, Keyphrase Extraction, Tagging etc. amongst other information extraction tasks.

Text annotation has the potential of enhancing a wide range of applications, including search, faceted browsing and navigation. By connecting text documents with DBpedia, our system enables a range of interesting use cases. For instance, the ontology can be used as background knowledge to display complementary information on web pages or to enhance information retrieval tasks. Moreover, faceted browsing over documents and customization of web feeds based on semantics become feasible. Finally, by following links from DBpedia into other data sources, the Linked Open Data cloud is pulled closer to the Web of Documents.

Take a look at our known uses page for other examples of how DBpedia Spotlight can be used. If you use DBpedia Spotlight in your project, please add a link to http://www.dbpedia-spotlight.org. If you use it in a paper, please use the citation.

You can try out DBpedia Spotlight through our web application or web service endpoints. The web application is a user interface that allows you to enter text in a form and generates an HTML annotated version of the text with links to DBpedia. The web service endpoints provide programmatic access to the demo, allowing you to retrieve data also in XML, JSON, JSON-LD, NIF and N3.