1. A computer-implemented method to extract and characterize features from unstructured data, the method comprising: evaluating a first feature of a plurality of features of unspecified type that are extracted from a first unstructured data element, based on one or more feature characterization rules and further based on a plurality of predefined feature types, to determine a measure of accuracy of a first feature type and a second feature type of the plurality of predefined feature types, respectively, in characterizing the first feature; upon determining that the measure of accuracy of the first feature type is greater than the measure of accuracy of the second feature type, characterizing the first feature as being an instance of the first feature type; reevaluating the first feature by operation of one or more computer processors and based the one or more feature characterization rules and the plurality of predefined feature types and further based on retrieved contextual information pertaining to a second feature of the plurality of extracted features, to determine whether the second feature type has a new measure of accuracy greater than the measure of accuracy of the first feature type; and upon determining that the new measure of accuracy of the second feature type is greater than the measure of accuracy of the first feature type, recharacterizing the first feature as being an instance of the second feature type; wherein a third feature corresponding to the first feature and extracted from a second unstructured data element is evaluated based on the one or more feature characterization rules, the plurality of predefined feature types, and retrieved contextual information pertaining to the third feature and including the second feature, the second feature type being stored as contextual information pertaining to the first feature.