Taggers for Parsers
Michael Littman, and
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.