POS Induction (State of the art)
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Latest revision as of 07:17, 25 June 2012
Contents |
Evaluation
Many-to-1: Map every induced label to a gold standard tag greedily (45 labels to 45 tags of the Penn tag set). Use the mapping to compute tag accuracy on the Wall Street Journal portion of the Penn TreeBank.
Results
| 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)
