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

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==Evaluation==
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'''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.
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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
 
|-
 
|-
| 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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<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 05:17, 25 June 2012

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