Difference between revisions of "POS Induction (State of the art)"

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* Yatbaz, Mehmet Ali, Enis Sert and Deniz Yuret. 2012. [http://aclweb.org/anthology//D/D12/D12-1086.pdf Learning Syntactic Categories Using Paradigmatic Representations of Word Context]. In Proceedings of EMNLP 2012, pages 940–951.
 
* Yatbaz, Mehmet Ali, Enis Sert and Deniz Yuret. 2012. [http://aclweb.org/anthology//D/D12/D12-1086.pdf Learning Syntactic Categories Using Paradigmatic Representations of Word Context]. In Proceedings of EMNLP 2012, pages 940–951.
  
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== Software ==
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* [http://www.cs.rhul.ac.uk/home/alexc/pos2.tar.gz alexc]
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* [https://github.com/percyliang/brown-cluster brown-cluster]
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* [http://www.statmt.org/moses/giza/mkcls.html mkcls]
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* [http://wortschatz.uni-leipzig.de/~cbiemann/software/unsupos.html unsupos]
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* [https://github.com/ai-ku/upos upos]
  
 
== See also ==
 
== See also ==

Revision as of 17:24, 7 March 2014

Evaluation

Many-to-1: Map every induced label to a gold standard tag greedily (45 labels to 45 tags of the Penn tag set). Use the mapping to compute tag accuracy on the Wall Street Journal portion of the Penn TreeBank.


Results

Listed in order of decreasing accuracy


System name Short description Main publications Software Many-to-1
UPOS Learning Syntactic Categories Using Paradigmatic Representations of Word Context Yatbaz et al. (2012) upos 80.2%
Brown+proto MRF initialized with Brown prototypes Christodoulopoulos, Goldwater and Steedman (2010) 76.1%
Logistic regression with features and LBFGS Berg-Kirkpatrick et al. (2010) 75.5%
Clark DMF Distributional clustering + morphology + frequency Clark (2003) alexc 71.2%*

* according to Christodoulopoulos, Goldwater and Steedman (2010)


References

Listed alphabetically.

Software

See also