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

From ACL Wiki
Jump to: navigation, search
m (POS Tagging (StateOfTheArt) moved to POS Tagging (State of the art): Wikipedia capitalization)
m (Wikipedia capitalization)
Line 8: Line 8:
  
 
{{StateOfTheArtTable}}
 
{{StateOfTheArtTable}}
| SVMTool || SVM Based tagger and tagger generator || Jesús Giménez and Lluís Márquez. SVMTool: A general POS tagger generator based on Support Vector Machines[http://www.lsi.upc.es/~nlp/SVMTool/lrec2004-gm.pdf] || [http://www.lsi.upc.es/~nlp/SVMTool/|http://www.lsi.upc.es/~nlp/SVMTool/ || 97.16% ||  
+
| SVMTool || SVM Based tagger and tagger generator || Jesús Giménez and Lluís Márquez. SVMTool: A general POS tagger generator based on Support Vector Machines [http://www.lsi.upc.es/~nlp/SVMTool/lrec2004-gm.pdf] || [http://www.lsi.upc.es/~nlp/SVMTool/ 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 [http://nlp.stanford.edu/kristina/papers/tagging.pdf] || [http://nlp.stanford.edu/software/tagger.shtml|http://nlp.stanford.edu/software/tagger.shtml] || 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% ||
 
|-
 
|-
  
Line 17: Line 17:
  
  
[[Category:State Of The Art]]
+
[[Category:State of the art]]

Revision as of 13:55, 18 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%