LODifier: Generating Linked Data from Unstructured Text
published: July 4, 2012, recorded: May 2012, views: 5470
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
The automated extraction of information from text and its transformation into a formal description is an important goal of in both Semantic Web research and computational linguistics. The extracted information can be used for a variety of tasks such as ontology generation, question answering and information retrieval. LODifier is an approach that combines deep semantic analysis with named entity recognition, word-sense disambiguation and controlled Semantic Web vocabularies in order to extract named entities and relations between them from text and to convert them into an RDF representation which is linked to DBpedia and WordNet. We present the architecture of our tool and discuss design decisions made. Evaluations of the tool give clear evidence of its potential for tasks like information extraction and computing document similarity.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !