Traditional Chinese dependency parser

Yen Hsuan Lee, Yih Ru Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recently, dependency parser has been paid highly attention in CoNLL conference, in this case we can find how important it is. However, there is no native Taiwanese attend to this competition. Therefore, we aim to build a traditional Chinese dependency parser in this paper. Through different famous neural network structure, such as multilayer perceptron and recurrent neural network along with traditional Chinese segmentation, we are able to construct an efficient parser that could transfer a raw traditional Chinese sentences to a dependency tree. We have much better result than similar task that has been proposed at 2012.

Original languageEnglish
Title of host publicationProceedings of the 30th Conference on Computational Linguistics and Speech Processing, ROCLING 2018
EditorsChi-Chun Lee, Cheng-Zen Yang, Jen-Tzung Chien, Chen-Yu Chiang, Min-Yuh Day, Richard T.-H. Tsai, Hung-Yi Lee, Wen-Hsiang Lu, Shih-Hung Wu
PublisherThe Association for Computational Linguistics and Chinese Language Processing (ACLCLP)
Pages61-75
Number of pages15
ISBN (Electronic)9789869576918
StatePublished - 1 Oct 2018
Event30th Conference on Computational Linguistics and Speech Processing, ROCLING 2018 - Hsinchu, Taiwan
Duration: 4 Oct 20185 Oct 2018

Publication series

NameProceedings of the 30th Conference on Computational Linguistics and Speech Processing, ROCLING 2018

Conference

Conference30th Conference on Computational Linguistics and Speech Processing, ROCLING 2018
CountryTaiwan
CityHsinchu
Period4/10/185/10/18

Keywords

  • Dependency parser
  • MultiLayer perceptron
  • Natural language processing
  • Recurrent neural network

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