From a user perspective it’s pretty simple: You hand the web service unstructured text (like news articles, blog postings, your term paper, etc) and it returns semantic metadata in RDF format. What’s happening in the background is a little more complicated.
Using natural language processing and machine learning techniques, the Calais web service looks inside your text and locates the entities (people, places, products, etc), facts (John Doe works for Acme Corp) and events (Jane Doe was appointed as a Board member of Acme Corp) in the text. Calais then processes the entities, facts and events extracted from the text and returns them to the caller in RDF format.
Of, course, they picked a name that sounds like one of those male enhancement drugs.
