9. A computer-readable non-transitory storage medium containing a classifier conversion application that, when executed, causes a computer to perform a method that converts an extant host language classifier on the computer to an initial target language classifier, the method comprising: translating un-marked target language examples from passages of target language text into un-marked host language examples, each example being an informational pair of a feature or features of the respective language and a classification result for that feature or feature; classifying the un-marked host language examples using the extant host language classifier on the computer based on marked host language examples included in the extant host language classifier; marking un-marked target language examples from the passages of target language text based on the classifying to obtain marked target language examples; building an initial target language classifier using the marked target language examples; re-classifying the marked target language examples in the initial target language classifier; questioning the marking used to obtain the marked target language examples in the initial target language classifier based on the re-classifying; isolating a high-quality set of marked target language examples based on the results of the questioning; and using the high-quality set of marked target language examples to improve the initial target language classifier.
9. A computer-readable non-transitory storage medium containing a classifier conversion application that, when executed, causes a computer to perform a method that converts an extant host language classifier on the computer to an initial target language classifier, the method comprising: translating un-marked target language examples from passages of target language text into un-marked host language examples, each example being an informational pair of a feature or features of the respective language and a classification result for that feature or feature; classifying the un-marked host language examples using the extant host language classifier on the computer based on marked host language examples included in the extant host language classifier; marking un-marked target language examples from the passages of target language text based on the classifying to obtain marked target language examples; building an initial target language classifier using the marked target language examples; re-classifying the marked target language examples in the initial target language classifier; questioning the marking used to obtain the marked target language examples in the initial target language classifier based on the re-classifying; isolating a high-quality set of marked target language examples based on the results of the questioning; and using the high-quality set of marked target language examples to improve the initial target language classifier. 12. The computer-readable storage medium of claim 9 , wherein the method further comprises: translating host language classifier data structures to obtain translated target language data structures; and using the translated target language data structures to build the initial target language classifier.