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Armadillo is a tool that provides automatic annotation for the Semantic Web using unannotated resources like the existing Web for information harvesting, that is: combining a crawling mechanism with an extensible architecture for ontology population. The latter is achieved via largely unsupervised machine learning, boot-strapped from oracles, such as web-site wrappers, and backed up by an 'Evidential reasoning', allowing evidence to be gained from the redundancy in the Web and allowing the inaccuracies in information, also characteristic of the Web, to be circumvented. This paper sketches how the Armadillo architecture has been reinterpreted as workflow templates that compose semantic web services and shows how the porting of Armadillo to new domains, and the application of new tools, has thus been simplified.

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