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Named Entity Recognition for German Using Conditional Random Fields and Linguistic Resources

Abstract : This paper presents a Named Entity Recognition system for German based on Conditional Random Fields. The model also includes language-independent features and features computed form large coverage lexical resources. Along side the results themselves, we show that by adding linguistic resources to a probabilistic model, the results improve significantly.
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https://hal-upec-upem.archives-ouvertes.fr/hal-01402574
Contributor : Matthieu Constant <>
Submitted on : Thursday, November 24, 2016 - 7:31:23 PM
Last modification on : Thursday, April 2, 2020 - 9:04:02 PM
Long-term archiving on: : Monday, March 20, 2017 - 5:42:34 PM

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  • HAL Id : hal-01402574, version 1

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Patrick Watrin, Louis de Viron, Denis Lebailly, Mathieu Constant, Stéphanie Weiser. Named Entity Recognition for German Using Conditional Random Fields and Linguistic Resources. GermEval 2014 Named Entity Recognition Shared Task - KONVENS 2014 Workshop, Oct 2014, Hildesheim, Germany. ⟨hal-01402574⟩

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