1. A method for evolving an annotating model for classifying a document or a data item therein, comprising: composing a first concept evolution model as a training set comprised of a first set of selectively determinable annotations detectable within the document and the first concept evolution model; training a learning algorithm with the training set and the concept evolution model to generate a trained model; using the trained model to predict classes for unlabeled elements within the document; computing a confidence factor that an predicted annotation is accurate; identifying an element instance and a corresponding suggested annotation having a low confidence factor; adjusting the classifying of the applied annotation wherein a second concept evolution model is composed for more accurate classifying of the data item.