“In that release we’ll go beyond the ability to extract semantic data from your content. We will link that extracted semantic data to datasets from dozens of other information sources, from Wikipedia to Freebase to the CIA World Fact Book. In short – instead of being limited to the contents of the document you’re processing, you’ll be able to develop solutions that leverage a large and rapidly growing information asset: the Linked Data Cloud.”

The new capabilities will be available in release 4 that is expected
out on 09 January 2009.

The change is based on Calais returning de-referenceable URIs for the entities it finds. Accessing those URIs will produce RDF with links to corresponding entities in DBpedia, Freebase and other sources of “Semantic Web” data. It will be very interesting to see how well their system does at mapping document entities (e.g., “secretary Rice”) to entities in the LOD cloud such as http://dbpedia.org/resource/Condoleezza_Rice. Accessing that URI with a request for content type application/rdf+xml returns the RDF at http://dbpedia.org/data/Condoleezza_Rice that has RDF assertions extracted by DBpedia from Wikipedia.

Freebase is “an open database of the world’s information” that is constructed by a Wiki-like collaborative community. In many ways it is like the Semantic Web model, with two big differences: (1) the data is stored centrally rather than distributed across the Web and (2) the representation system is not based on RDF but rather uses a custom built object-oriented data representation language.

Freebase is a great resource. Much of the data is extracted from Wikipedia, so its content has a large overlap with DBpedia. But it is also relatively easy to upload additional information in various structured forms and many have done so, resulting in an extended coverage.

This is clearly a system in the Web of Data space along with the Linking Open Data effort and having it should offer a way for us all to explore the consequences of some of the underlying design decisions.