1. A computer-implemented method, comprising: extracting by a processor instances from a plurality of sources using a plurality of knowledge extractors; aggregating the instances from the plurality of sources; extracting a plurality of feature vectors for a plurality of instances using a plurality of feature generators, each feature vector extracted by a plurality of feature generators; and building a model by using a modeler based, at least in part, upon the feature vectors extracted by the plurality of feature generators and extracted instances, wherein building the model comprises automatically generating training sets of instances.
4. The computer-implemented method of claim 1 , wherein building the decoder further comprises utilizing external positive instances in generating at least a portion of the training sets.