When trained on unigram word token models only we observed a decrease in performance of about 10% compared to the performance using the combined features; trained on n-gram POS tag models 5% on average; and trained on n-gram chunking information 20%.
wording of an utterance is still very important, but, when supplied with linguistic information, the performance of the classifier improves.