@inproceedings{92794dcdd01440569b2592ad759ae737,
title = "High Quality Dependency Selection from Automatic Parses",
abstract = "Many NLP tasks such as question answering and knowledge acquisition are tightly dependent on dependency parsing. Dependency parsing accuracy is always decisive for the performance of subsequent tasks. Therefore, reducing dependency parsing errors or selecting high quality dependencies is a primary issue. In this paper, we present a supervised approach for automatically selecting high quality dependencies from automatic parses. Experimental results on three different languages show that our approach can effectively select high quality dependencies from the result analyzed by a dependency parser.",
author = "Gongye Jin and Daisuke Kawahara and Sadao Kurohashi",
note = "Publisher Copyright: {\textcopyright} IJCNLP 2013.All right reserved.; 6th International Joint Conference on Natural Language Processing, IJCNLP 2013 ; Conference date: 14-10-2013",
year = "2013",
language = "English",
series = "6th International Joint Conference on Natural Language Processing, IJCNLP 2013 - Proceedings of the Main Conference",
publisher = "Asian Federation of Natural Language Processing",
pages = "947--951",
editor = "Ruslan Mitkov and Park, {Jong C.}",
booktitle = "6th International Joint Conference on Natural Language Processing, IJCNLP 2013 - Proceedings of the Main Conference",
}