Moreover, rule-based NLP approaches also have their place, and they are often the direct result of theoretical advances. A case in point is the modelling of morphophonology (which is necessary for spell checking, dictionaries and text generation for morphologically complex languages): many successful approaches are those based on finite-state machines, which could not have happened without Johnson and later Koskenniemi using them to formalize the rule-based approach pioneered by Halle and (yes) Chomsky (well, not quite, but this is still the point of reference for rule-based phonology).
(I am a theoretical phonologist, but my colleagues who do actual NLP work of this type tell me that statistical methods aren't that great for the sort of work they do.)