10. A system, comprising: a processor; logic encoded in one or more tangible media for execution by the processor, the logic when executed by the processor causing the system to perform operations comprising: receiving annotated documents comprising annotated fields; analyzing the annotated documents to determine contextual information for each of the annotated fields; determining discriminative sequences using the contextual information by: aligning pairs of strings having possible contextual matches; normalizing the pairs of strings by extracting matching segments having a given length; aggregating the normalized pairs of strings; and applying a greedy contiguity heuristic to the aggregated normalized pairs of strings, wherein the greedy contiguity heuristic is used by the system to evaluate any of a number of matching segments, a number of gaps between segments, and variances between segment lengths; determining longest contiguous common subsequences between aligned pairs of strings of the annotated documents; determining a frequency of occurrence of similar longest contiguous common subsequences; and generating a proposed rule or a feature set from longest contiguous common subsequences having a desired frequency of occurrence; and an extractor system that trains a classifier model using the feature set.
16. The system according to claim 10 , further comprising a feature-based extractor generator that converts the feature set into a feature-based vector.