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Effective semantic relationship classification of context-free Chinese words with simple surface and embedding features

  • Yunxiao Zhou
  • , Man Lan*
  • , Yuanbin Wu
  • *此作品的通讯作者
  • East China Normal University
  • Shanghai Key Laboratory of Multidimensional Information Processing

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

This paper describes the system we submitted to Task 1, i.e., Chinese Word Semantic Relation Classification, in NLPCC 2017. Given a pair of context-free Chinese words, this task is to predict the semantic relationships of them among four categories: Synonym, Antonym, Hyponym and Meronym. We design and investigate several surface features and embedding features containing word level and character level embeddings together with supervised machine learning methods to address this task. Officially released results show that our system ranks above average.

源语言英语
主期刊名Natural Language Processing and Chinese Computing - 6th CCF International Conference, NLPCC 2017, Proceedings
编辑Xuanjing Huang, Jing Jiang, Dongyan Zhao, Yansong Feng, Yu Hong
出版商Springer Verlag
456-464
页数9
ISBN(印刷版)9783319736174
DOI
出版状态已出版 - 2018
活动6th CCF International Conference on Natural Language Processing and Chinese Computing, NLPCC 2017 - Dalian, 中国
期限: 8 11月 201712 11月 2017

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
10619 LNAI
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议6th CCF International Conference on Natural Language Processing and Chinese Computing, NLPCC 2017
国家/地区中国
Dalian
时期8/11/1712/11/17

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