We propose a two-fold approach that is able to both consume and exploit semantics encoded in the Linking Open Data (LOD) cloud, and create news that document events reported in micro-blogging posts that correspond to
tweets. A documentary tweet is similar to a newspaper headline and reports an incident or event. Knowledge extracted from documentary tweets are used to develop a story line which will be augmented with RDF facts consumed from the LOD cloud. The resulting news content is represented in RDF using the
, facilitating news generation and retrieval. We study effectiveness of our approach with respect to a gold standard of manually tagged tweets. Initial experimental results suggest that our techniques are able to generate content that reflects up to 76.38% of the manually tagged terms.