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Maximum Entropy Part-of-Speech Tagging in NLTK

In this paper we implement a part of speech tagger for NLTK using maximum entropy methods. Our tagger can be used as a drop-in replacement for any of the other NLTK taggers. We give a brief tutorial on how to use our tagger as well as describing the implementation at a high level. We evaluate our tagger on the Penn Tree Bank and compare our results to those of previous work.