On WordNet Semantic Classes and Dependency Parsing

被引：0

作者：

Bengoetxea, Kepa ^{[1
]}

Agirre, Eneko ^{[1
]}

Nivre, Joakim ^{[2
]}

Zhang, Yue ^{[3
]}

Gojenola, Koldo ^{[1
]}

机构：

[1] Univ Basque Country, UPV EHU, IXA NLP Grp, Leioa, Spain

[2] Uppsala Univ, Dept Linguist & Philol, Uppsala, Sweden

[3] Singapore Univ Technol & Design, Singapore, Singapore

来源：

PROCEEDINGS OF THE 52ND ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, VOL 2 | 2014年

关键词：

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This paper presents experiments with WordNet semantic classes to improve dependency parsing. We study the effect of semantic classes in three dependency parsers, using two types of constituency-to-dependency conversions of the English Penn Treebank. Overall, we can say that the improvements are small and not significant using automatic POS tags, contrary to previously published results using gold POS tags (Agirre et al., 2011). In addition, we explore parser combinations, showing that the semantically enhanced parsers yield a small significant gain only on the more semantically oriented LTH treebank conversion.

引用

页码：649 / 655

页数：7

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