We propose a novel language-independent
framework for inducing a collection of morphological
inflection classes from a monolingual
corpus of full form words. Our approach
involves two main stages. In the first stage,
we generate a large data structure of candidate
inflection classes and their interrelationships.
In the second stage, search and filtering techniques
are applied to this data structure, to
identify a select collection of "true" inflection
classes of the language. We describe the basic
methodology involved in both stages of our
approach and present an evaluation of our
baseline techniques applied to induction of
major inflection classes of Spanish. The preliminary
results on an initial training corpus
already surpass an F1 of 0.5 against ideal
Spanish inflectional morphology classes.