7. A program storage device readable by machine, tangibly embodying a program of instructions executable by the machine to perform method steps for processing natural language text, the method steps comprising: receiving as input a natural language text sentence comprising a sequence of white-space delimited words including inflicted words that are formed of morphemes including a stem and one or more affixes; automatically parsing the inflicted words into their constituent morphemes; grouping the parsed morphemes of the inflicted words with the same syntactic role into constituents; identifying a plurality of verb-constituent pairs in the text sentence, wherein at least one verb-constituent pair is formed of respective morphemes of a same white-space delimited word; predicting potential arguments for each constituent of the grouped morphemes, wherein the constituents are associated with a verb by the verb-constituent pairs; and predicting a semantic role of each constituent of the grouped morphemes according to probabilities of the potential arguments, wherein predicting potential arguments for each constituent of the grouped morphemes and predicting the semantic role of each constituent of the grouped morphemes according to the probabilities of each of the potential arguments includes: performing lexical/surface analysis; performing morphological analysis; performing semantic analysis; performing syntactic analysis; and integrating results of the lexical/surface analysis, the morphological analysis, the semantic analysis, and the syntactic analysis into a statistical model based on Maximum Entropy to produce a probability model for predicting potential arguments for each constituent of the grouped morphemes and predicting the semantic role of each constituent of the grouped morphemes according to the probabilities of each of the potential arguments.
13. The program storage device of claim 7 , wherein the instructions for predicting potential arguments for each constituent, comprise instructions for: determining a likelihood of a semantic role of a constituent for the target verb over a set of possible semantic roles given the identified target verb; and assigning the constituent a semantic role label having the highest likelihood over the set of possible semantic roles.