A Case Study in Part-of-Speech Tagging Using the ICOPOST Toolkit

Part-of-speech tagging is an important processing step for many natural language systems. It has been tackled with a number of different approaches, both machine learning algorithms and methods relying on rules that are hand crafted by human experts. This paper investigates and compares four of the more popular machine learning approaches to POS tagging that have been implemented within the ICOPOST toolkit which is freely available under the GNU public license from the author's home page at http://nats-www.informatik.uni-hamburg.de/~ingo/icopost/.