In computational linguistics, efficient recognition of
phrases is an important prerequisite for many ambitious goals,
such as automated extraction of terminology,
part of speech disambiguation, and automated translation. If one wants
to recognize
a certain well-defined set of phrases, the question of which type of computational
device to use for this task arises. For sets of phrases that are not
too complex, as well
as for many subtasks of the recognition process, finite state methods
are appropriate
and favourable because of their efficiency Gross and Perrin 1989; Silberztein
1993;
Tapanainen 1995. However, if very large sets of possibly complex phrases
are
considered where correct resolution of grammatical structure requires morphological
analysis (e.g. verb argument structure, extraposition of relative
clauses, etc.), then the
design and implementation of an appropriate finite state automaton might
turn out
to be infeasible in practice due to the immense number of morphological
variants
to be captured.