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The SVMTool is a simple and effective generator of sequential taggers based on Support Vector Machines. We have appied the SVMTool to the problem of part-of-speech (PoS) tagging. By means of a rigorous experimental evaluation, we conclude that the proposed SVM-based tagger is robust and flexible for feature modelling (including lexicalization), trains efficiently with almost no parameters to tune, and is able to tag thousands of words per second, which makes it really practical for real NLP applications. Regarding accuracy, the SVM-based tagger significantly outperforms the TnT tagger exactly under the same conditions, and achieves a very competitive accuracy of 97.2% for English on the Wall Street Journal corpus, which is comparable to the best taggers reported up to date.
The SVMlight software implementation of Vapnik's Support Vector Machine [Vapnik, 1995] by Thosten Joachims has been used to train the models. For further information on it see:
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application models for PoS Tagging docs
SVMTool Discussion Group
Discussion on features and bugs of this software as well as information
about oncoming updates takes place on the SVMTool group, to which
you can subscribe at:
http://groups.google.es/group/svmt
and post messages at:
SVMT at googlegroups.com
Contributing
The SVMTool library is released under the GNU Lesser General Public License (LGPL) of the Free Software Foundation. This means that it may be linked to and used by commercial software packages. But the license also enforces that any changes or improvements made to the library (and in this case also to the morphological data) must be redistributed under LGPL terms.
Thus, if you improve the software or data, either adding new functionalities, fixing bugs, or building sequential taggers on different data, you can not distribute them under different conditions than those stated in the license (i.e. freely and with no usage restrictions).
If you want that your changes and improvements become useful to many other people using this free software, please contact us (
References
Please reference this tool in your academic works citing the following
paper: