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

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| Stanford Tagger || Learning with Cyclic Dependency Network || Kristina Toutanova, Dan Klein, Christopher D. Manning, and Yoram Singer. Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network [http://nlp.stanford.edu/kristina/papers/tagging.pdf] || [http://nlp.stanford.edu/software/tagger.shtml tagger] || 97.24% ||
 
| Stanford Tagger || Learning with Cyclic Dependency Network || Kristina Toutanova, Dan Klein, Christopher D. Manning, and Yoram Singer. Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network [http://nlp.stanford.edu/kristina/papers/tagging.pdf] || [http://nlp.stanford.edu/software/tagger.shtml tagger] || 97.24% ||
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|  || Bidirectional Perceptron Learning || Libin Shen, Giorgio Satta and Aravind K. Joshi.  Guided Learning for Bidirectional Sequence Classification  [http://acl.ldc.upenn.edu/P/P07/P07-1096.pdf] || [http://www.cis.upenn.edu/~xtag/spinal/ POS tagger] || 97.33% ||
 
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Revision as of 07:21, 20 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 Jesús Giménez and Lluís Márquez. SVMTool: A general POS tagger generator based on Support Vector Machines [1] SVMTool 97.16%
Stanford Tagger Learning with Cyclic Dependency Network Kristina Toutanova, Dan Klein, Christopher D. Manning, and Yoram Singer. Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network [2] tagger 97.24%
Bidirectional Perceptron Learning Libin Shen, Giorgio Satta and Aravind K. Joshi. Guided Learning for Bidirectional Sequence Classification [3] POS tagger 97.33%