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

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("Standard" datasets:)
("Standard" datasets:)
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{{StateOfTheArtTable}}
 
{{StateOfTheArtTable}}
| SVMTool || SVM Based tagger and tagger generator || Giménez and Márquez (2004) || [http://www.lsi.upc.es/~nlp/SVMTool/ SVMTool] || 97.16% ||  
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| SVMTool || SVM-based tagger and tagger generator || Giménez and Márquez (2004) || [http://www.lsi.upc.es/~nlp/SVMTool/ SVMTool] || 97.16% ||  
 
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| Stanford Tagger || Learning with Cyclic Dependency Network || Toutanova et al. (2003) || [http://nlp.stanford.edu/software/tagger.shtml Stanford Tagger] || 97.24% ||
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| Stanford Tagger || learning with cyclic dependency network || Toutanova et al. (2003) || [http://nlp.stanford.edu/software/tagger.shtml Stanford Tagger] || 97.24% ||
 
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| POS tagger || Bidirectional Perceptron Learning || Shen et al. (2007)  || [http://www.cis.upenn.edu/~xtag/spinal/ POS tagger] || 97.33% ||
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| POS tagger || bidirectional perceptron learning || Shen et al. (2007)  || [http://www.cis.upenn.edu/~xtag/spinal/ POS tagger] || 97.33% ||
 
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Giménez, J., and Márquez, L. (2004). [http://www.lsi.upc.es/~nlp/SVMTool/lrec2004-gm.pdf SVMTool: A general POS tagger generator based on Support Vector Machines].
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Giménez, J., and Márquez, L. (2004). [http://www.lsi.upc.es/~nlp/SVMTool/lrec2004-gm.pdf SVMTool: A general POS tagger generator based on Support Vector Machines]. ''Proceedings of the 4th International Conference on Language Resources and Evaluation (LREC'04)''. Lisbon, Portugal.  
  
 
Shen, L., Satta, G., and  Joshi, A. (2007). [http://acl.ldc.upenn.edu/P/P07/P07-1096.pdf Guided learning for bidirectional sequence classification]. ''Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics (ACL 2007)'', pages 760-767.
 
Shen, L., Satta, G., and  Joshi, A. (2007). [http://acl.ldc.upenn.edu/P/P07/P07-1096.pdf Guided learning for bidirectional sequence classification]. ''Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics (ACL 2007)'', pages 760-767.

Revision as of 11:11, 21 June 2007

"Standard" measure:

  • Per token accuracy

"Standard" datasets:

  • Training: sections 0-18 of WSJ
  • Testing: sections 22-24 of WSJ


System Name Short Description Main Publications Software (if available) Results Comments (i.e. extra resources used, train/test times, ...)
SVMTool SVM-based tagger and tagger generator Giménez and Márquez (2004) SVMTool 97.16%
Stanford Tagger learning with cyclic dependency network Toutanova et al. (2003) Stanford Tagger 97.24%
POS tagger bidirectional perceptron learning Shen et al. (2007) POS tagger 97.33%


Giménez, J., and Márquez, L. (2004). SVMTool: A general POS tagger generator based on Support Vector Machines. Proceedings of the 4th International Conference on Language Resources and Evaluation (LREC'04). Lisbon, Portugal.

Shen, L., Satta, G., and Joshi, A. (2007). Guided learning for bidirectional sequence classification. Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics (ACL 2007), pages 760-767.

Toutanova, K., Klein, D., Manning, C.D., Yoram Singer, Y. (2003) Feature-rich part-of-speech tagging with a cyclic dependency network. Proceedings of HLT-NAACL 2003, pages 252-259.