The World Wide Web is currently one of the most popular platforms for publishing, disseminating and consuming news. However, the huge number of daily published news items brings new challenges for both readers and publishers of web news systems in the process of finding or arranging information. In this paper, we present a method for generating automatically semantic annotations of sport news items. It combines the results obtained through our continuous study of capturing different kinds of semantics which having from simple to more complex representation structure. Our approach relies on the detection of named entities as the ontology instances using knowledge base on sport. The instances are matched with pre-defined patterns to extract semantics. Experiments on corpus of sport news validates the advantages of the proposed method and shows that semantic annotations are generated with high precision and coverage.
Keyword
semantic annotation, semantic web, knowledge base, named entity recognition
