  In this paper we compare two competing approaches to part-of-speech tagging,
statistical and constraint-based disambiguation, using French as our test
language. We imposed a time limit on our experiment: the amount of time spent
on the design of our constraint system was about the same as the time we used
to train and test the easy-to-implement statistical model. We describe the two
systems and compare the results. The accuracy of the statistical method is
reasonably good, comparable to taggers for English. But the constraint-based
tagger seems to be superior even with the limited time we allowed ourselves for
rule development.
