11. The method for resolving natural language ambiguities within text documents of claim 1 , further comprising determining discourse categories of said text documents using a discourse category analysis module whereby additional contextual features are extracted.
12. The method for determining discourse categories of claim 11 , comprising the following steps of: training probabilistic discourse category classifiers using annotated training data containing discourse categories for each document; determining discourse categories of said text documents by maximizing the probability computed using said probabilistic discourse category classifiers based on contextual features; and integrating additional contextual features as generated by one or more of the following natural language processing modules into said probabilistic classifiers whereby said measure of confidence is improved: using a word sense disambiguation module to determine word senses and the associated measure of confidence for each word; using a chunking module to identify multi-word phrases and the associated measure of confidence for each phrase; using a named-entity recognition module to identify named entities and the associated measure of confidence for each entity; using a syntactic parsing module to construct sentential parse trees and the associated measure of confidence for each tree; using an anaphora resolution module to identify anaphor references and the associated measure of confidence for each reference; using a discourse structure analysis module to determine discourse structures and the associated measure of confidence for each structure.