Improving POS Tagging of German Learner Language in a Reading Comprehension Scenario

被引：0

作者：

Keiper, Lena ^{[1
]}

Horbach, Andrea ^{[1
]}

Thater, Stefan ^{[1
]}

机构：

[1] Saarland Univ, Dept Computat Linguist, Saarbrucken, Germany

来源：

LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION | 2016年

关键词：

Part-of-Speech Tagging; Learner Language; Corpus Annotation;

D O I：

暂无

中图分类号：

H [语言、文字];

学科分类号：

05 ;

摘要：

We present a novel method to automatically improve the accurrcy of part-of-speech taggers on learner language. The key idea underlying our approach is to exploit the structure of a typical language learner task and automatically induce POS information for out-of-vocabulary (OOV) words. To evaluate the effectiveness of our approach, we add manual POS and normalization information to an existing language learner corpus. Our evaluation shows an increase in accuracy from 72.4% to 81.5% on OOV words.

引用

页码：198 / 205

页数：8

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