9. The method for resolving natural language ambiguities within text documents of claim 1 , further comprising resolving anaphora references of said text documents using an anaphora resolution module whereby additional contextual features are extracted.
9. The method for resolving natural language ambiguities within text documents of claim 1 , further comprising resolving anaphora references of said text documents using an anaphora resolution module whereby additional contextual features are extracted. 10. The method for resolving anaphora references of claim 9 , comprising the following steps of: training a probabilistic anaphora-alignment classifier using training data containing anaphora to antecedent annotations; determining an anaphor to antecedent alignment for each anaphor in said text documents by maximizing the probability computed using said probabilistic anaphora-alignment classifier 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 a discourse categorization module to determine document categories and the associated measure of confidence for each category; using a discourse structure analysis module to determine discourse structures and the associated measure of confidence for each structure.