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ASV Toolbox - Viterbitagger 
Persistent Identifier of this resource:
http://urn.fi/urn:nbn:fi:lb-20140730148
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Train, use and evaluate a simple POS tagger.
This simple tagger implementation is based on tag trigrams and tag distributions for words. Not as powerful as a full HMM implementation, it comes with a morphological back-off component (realized with Pretree) and is capable of training tagger models on very large annotated texts in flexible formats. Further, it allows tagging previously tagged text with a second (e.g. semantic) tag. The format of the tagger model is readable as plain text, which could prove useful for educational purposes. An evaluation framework is included that also deals with evaluating on different tag sets for Gold standard and test. Supervised models are provided for English, German and Finnish, unsupervised tagger models for resource-scarce languages or domain-specific applications are available at http://wortschatz.uni-leipzig.de/~cbiemann/software/unsupos.html
This simple tagger implementation is based on tag trigrams and tag distributions for words. Not as powerful as a full HMM implementation, it comes with a morphological back-off component (realized with Pretree) and is capable of training tagger models on very large annotated texts in flexible formats. Further, it allows tagging previously tagged text with a second (e.g. semantic) tag. The format of the tagger model is readable as plain text, which could prove useful for educational purposes. An evaluation framework is included that also deals with evaluating on different tag sets for Gold standard and test. Supervised models are provided for English, German and Finnish, unsupervised tagger models for resource-scarce languages or domain-specific applications are available at http://wortschatz.uni-leipzig.de/~cbiemann/software/unsupos.html
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