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

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(Berg-Kirkpatrick et al. (2010))
(Alexander Clark. 2003)
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==Evaluation==
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'''Many-to-1:''' Mapping every induced label to a gold standard tag greedily. Use the mapping to compute tag accuracy on the Wall Street Journal part of the Penn TreeBank.
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==Results==
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{| border="1" cellpadding="5" cellspacing="1" width="100%"
 
{| border="1" cellpadding="5" cellspacing="1" width="100%"
 
|-
 
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! Many-to-1
 
! Many-to-1
 
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|-
| Prototype-based+Brown
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| Brown+proto
 
| MRF initialized with Brown prototypes
 
| MRF initialized with Brown prototypes
 
| Christodoulopoulos, Goldwater and Steedman (2010)
 
| Christodoulopoulos, Goldwater and Steedman (2010)
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|  
 
|  
 
| 75.5%
 
| 75.5%
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|-
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| Clark DMF
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| Distributional clustering + morphology + frequency
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| Clark (2003)
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| [http://www.cs.rhul.ac.uk/home/alexc/pos2.tar.gz alexc]
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| 71.2%*
 
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|-
 
|}
 
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<nowiki>*</nowiki> according to Christodoulopoulos, Goldwater and Steedman (2010)
  
 
== References ==
 
== References ==
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* [http://www.aclweb.org/anthology/N/N10/N10-1083.pdf Taylor Berg-Kirkpatrick, Alexandre Bouchard-Cote, John DeNero, and Dan Klein. 2010. Painless Unsupervised Learning with Features. NAACL 2010.]
 
* [http://www.aclweb.org/anthology/N/N10/N10-1083.pdf Taylor Berg-Kirkpatrick, Alexandre Bouchard-Cote, John DeNero, and Dan Klein. 2010. Painless Unsupervised Learning with Features. NAACL 2010.]
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* [http://www.aclweb.org/anthology/E/E03/E03-1009.pdf Alexander Clark. 2003. Combining distributional and morphological information for part of speech induction. In Proceedings of EACL 2003, pages 59–66, Morristown, NJ, USA.]
  
 
== See also ==
 
== See also ==

Revision as of 14:43, 27 January 2011

Evaluation

Many-to-1: Mapping every induced label to a gold standard tag greedily. Use the mapping to compute tag accuracy on the Wall Street Journal part 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