https://www.aclweb.org/aclwiki/api.php?action=feedcontributions&feedformat=atom&user=Xtag 2026-06-09T06:01:45Z User contributions MediaWiki 1.43.6 https://www.aclweb.org/aclwiki/index.php?title=POS_Tagging_(State_of_the_art)&diff=3849 2007-06-20T14:21:55Z

<p>Xtag: Add (Shen, Satta and Joshi, 2007)</p> <hr /> <div>== &quot;Standard&quot; measure: ==<br /> * Per token accuracy<br /> <br /> == &quot;Standard&quot; datasets: ==<br /> * Training: sections 0-18 of WSJ<br /> * Testing: sections 22-24 of WSJ<br /> <br /> <br /> {{StateOfTheArtTable}}<br /> | 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% || <br /> |-<br /> <br /> | 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% ||<br /> |-<br /> <br /> | || 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% ||<br /> |-<br /> <br /> |}<br /> <br /> <br /> [[Category:State of the art]]</div>

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