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

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Revision as of 10:07, 16 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] http://www.lsi.upc.es/~nlp/SVMTool/ 97.16%
--- 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] No 97.24%