Check out:
http://www.cs.brown.edu/people/ec/papers/tagforpar.ps
from the abstract:
>
We consider what tagging models are most appropriate as front ends for
probabilistic context-free-grammar parsers. In particular we ask if using
a tagger that returns
more than one tag, a ``multple tagger,'' improves parsing performance. Our
conclusion is somewhat surprising: single tag Markov-model taggers are
quite adequate for
the task. First of all, parsing accuracy, as measured by the correct
assignment of parts of speech to words, does not increase significantly
when parsers select the tags
themselves. In addition, the work required to parse a sentence goes up
with increasing tag ambiguity, though not as much as one might expect.
Thus, for the moment,
single taggers are the best taggers.
>
Miles Osborne
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