  The performance of machine learning algorithms can be improved by combining
the output of different systems. In this paper we apply this idea to the
recognition of noun phrases.We generate different classifiers by using
different representations of the data. By combining the results with voting
techniques described in (Van Halteren et.al. 1998) we manage to improve the
best reported performances on standard data sets for base noun phrases and
arbitrary noun phrases.
