The evolution of the traditional Web into a Semantic Web and the continuous increase in the amount of data published as Linked Data open up new opportunities for annotation and categorization systems to reuse these data as semantic knowledge bases. Accordingly, Linked Data has been used by information extraction systems to exploit the semantic knowledge bases, which can be interconnected and structured in order to increase the precision and recall of annotation and categorization mechanisms. This paper describes TellMeFirst a software for the classification and enrichment of textual documents written in English and Italian. Although nowadays there are various works presenting solutions for text annotation and classification, this work is focused on describing and studying the use case of a Telecommunications Operator that has adopted TellMeFirst in order to generate value-added to two services available to its users: FriendTV and SOCIETY.
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