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RDRPOSTagger

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RDRPOSTagger is a robust and easy-to-use toolkit for POS and morphological tagging. It employs an error-driven approach to automatically construct tagging rules in the form of a binary tree.

The general architecture and experimental results of RDRPOSTagger can be found in our following papers:

Please CITE either the EACL or the AICom paper whenever RDRPOSTagger is used to produce published results or incorporated into other software.

Current release (41MB .zip file containing about 330 pre-trained tagging models) is available to download at: https://github.com/datquocnguyen/RDRPOSTagger/archive/master.zip

Find more information about RDRPOSTagger at: http://rdrpostagger.sourceforge.net/

In addition, you might want to try my neural network-based toolkit jPTDP for joint POS tagging and dependency parsing.