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

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| bidirectional perceptron learning
 
| bidirectional perceptron learning
 
| Shen et al. (2007)
 
| Shen et al. (2007)
| [http://www.cis.upenn.edu/~xtag/spinal/ POS tagger]
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| [http://www.cis.upenn.edu/~xtag/spinal/ LTAG-spinal]
 
| 97.33%
 
| 97.33%
 
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Revision as of 23:45, 18 November 2009

  • Performance measure: per token accuracy
  • Training data: sections 0-18 of Wall Street Journal corpus
  • Testing data: sections 22-24 of Wall Street Journal corpus


Table of results

System name Short description Main publications Software Results
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) LTAG-spinal 97.33%
GENiA Tagger  ? Tsuruoka, et al (2005) GENiA 96.94% on WSJ, 98.26% on biomed.

References

See also