  Text corpora which are tagged with part-of-speech information are useful in
many areas of linguistic research. In this paper, a new part-of-speech tagging
method based on neural networks (Net- Tagger) is presented and its performance
is compared to that of a HMM-tagger and a trigram-based tagger. It is shown
that the Net- Tagger performs as well as the trigram-based tagger and better
than the HMM-tagger.
