POS Induction (State of the art)

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| MRF initialized with Brown prototypes
 
| MRF initialized with Brown prototypes
 
| Christodoulopoulos, Goldwater and Steedman (2010)
 
| Christodoulopoulos, Goldwater and Steedman (2010)
| [http://www.thai-sbobet.com sbo]
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|  
 
| 76.1%
 
| 76.1%
 
|-
 
|-
| [http://www.thai-sbobet.com sbobet]
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|  
 
| Logistic regression with features and LBFGS
 
| Logistic regression with features and LBFGS
 
| Berg-Kirkpatrick et al. (2010)
 
| Berg-Kirkpatrick et al. (2010)

Revision as of 07:17, 25 June 2012

Contents

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

System name Short description Main publications Software Many-to-1
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

See also

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