Hi,

did you train new models for the ClearNLP/OpenNLP tools? (Maybe I knew if I had 
followed a past discussion on models more closely…)

Cheers,

-- Richard

Am 08.04.2013 um 18:15 schrieb "Chen, Pei" <[email protected]>:

> Hi,
> While working on the Dependency Parser/SRL labeler,  we also have a POSTagger 
> from ClearNLP.  It is fairly simple and I have the code ready (also trained 
> on the same data as the dep parser- MiPaq/SHARP) to be checked-in.  What does 
> the folks think:
> We can include both Analysis Engines in the ctakes-pos-tagger project.  But 
> should we leave the current OpenNLP in the default pipeline or default to the 
> latest?
> 
> "The ClearNLP POS tagger shows more robust results on unknown words by 
> generalizing lexical features.  You can find the reference from this paper.
> Fast and Robust Part-of-Speech Tagging Using Dynamic Model Selection, Jinho 
> D. Choi, Martha Palmer, Proceedings of the 50th Annual Meeting of the 
> Association for Computational Linguistics (ACL'12), 363-367, Jeju, Korea, 
> 2012. [1] It also uses AdaGrad for machine learning, which is a more advanced 
> learning algorithm than maximum entropy used by OpenNLP."
> 
> [1] http://aclweb.org/anthology-new/P/P12/P12-2071.pdf


-- 
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Richard Eckart de Castilho
Technical Lead
Ubiquitous Knowledge Processing Lab (UKP-TUD) 
FB 20 Computer Science Department      
Technische Universität Darmstadt 
Hochschulstr. 10, D-64289 Darmstadt, Germany 
phone [+49] (0)6151 16-7477, fax -5455, room S2/02/B117
[email protected] 
www.ukp.tu-darmstadt.de 
Web Research at TU Darmstadt (WeRC) www.werc.tu-darmstadt.de
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