POS Induction (State of the art)
Revision as of 17:43, 27 January 2011 by Auser
Many-to-1: Mapping every induced label to a gold standard tag greedily. Use the mapping to compute tag accuracy on the Wall Street Journal part of the Penn TreeBank.
|System name||Short description||Main publications||Software||Many-to-1|
|Brown+proto||MRF initialized with Brown prototypes||Christodoulopoulos, Goldwater and Steedman (2010)||76.1%|
|Logistic regression with features and LBFGS||Berg-Kirkpatrick et al. (2010)||75.5%|
|Clark DMF||Distributional clustering + morphology + frequency||Clark (2003)||alexc||71.2%*|
* according to Christodoulopoulos, Goldwater and Steedman (2010)
- Christos Christodoulopoulos, Sharon Goldwater and Mark Steedman. 2010. Two Decades of Unsupervised POS induction: How far have we come? In Proceedings of EMNLP 2010.
- Taylor Berg-Kirkpatrick, Alexandre Bouchard-Cote, John DeNero, and Dan Klein. 2010. Painless Unsupervised Learning with Features. NAACL 2010.
- Alexander Clark. 2003. Combining distributional and morphological information for part of speech induction. In Proceedings of EACL 2003, pages 59–66, Morristown, NJ, USA.