  We describe an automated method for identifying classes of morphologically
related words in an on-line dictionary, and for linking individual senses in
the derived form to one or more senses in the base form by means of
morphological relation attributes. We also present an algorithm for computing a
score reflecting the system=92s certainty in these derivational links; this
computation relies on the content of semantic relations associated with each
sense, which are extracted automatically by parsing each sense definition and
subjecting the parse structure to automated semantic analysis. By processing
the entire set of headwords in the dictionary in this fashion we create a large
set of directed derivational graphs, which can then be accessed by other
components in our broad-coverage NLP system. Spurious or unlikely derivations
are not discarded, but are rather added to the dictionary and assigned a
negative score; this allows the system to handle non-standard uses of these
forms.
