The paper proposes a paradigmatic approach to morphological knowledge acquisition. It addresses the problem of learning from examples rules for word-forms analysis and synthesis. These rules, established by generalizing the training data sets, are effectively used by a built-in interpreter which acts consequently as a morphological processor within the architecture of a natural language question-answering system. The PARADIGM system has no a priori knowledge which should restrict it to a particular natural language, but instead builds up the morphological rules based only on the examples provided, be they in Romanian, English, French, Russian, SIovak and the like.