Parsing chinese with head-driven model

Hai Long Cao; Tie Jun Zhao; Mu Yun Yang; Sheng Li

Parsing chinese with head-driven model

Hai Long Cao^*
, Tie Jun Zhao
, Mu Yun Yang
, Sheng Li

^*Corresponding author for this work

School of Computer Science and Technology, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

8 Scopus citations

Abstract

Great progress has been made in parsing the Wall Street Journal portion of the Penn Treebank. Now parsing languages other than English is an intensive research area. Head-driven model is one of the best English parsing models. It has been successfully applied to Czech but failed to outperform a baseline model in parsing German. This paper attempts to parse Chinese with head-driven model. Promising experimental results demonstrate that head-driven model works well for Chinese. We propose a hybrid parsing strategy, which combines head-driven model with a Chinese base phrases parsing model. The combined model not only improves the performance but also makes the parser space and time efficient. We evaluate our method in PARSEVAL measures, and the combined model performances are at 79.88% precision, 81.97% recall.

Original language	English
Title of host publication	Proceedings of 2004 International Conference on Machine Learning and Cybernetics
Pages	2618-2622
Number of pages	5
State	Published - 2004
Externally published	Yes
Event	Proceedings of 2004 International Conference on Machine Learning and Cybernetics - Shanghai, China Duration: 26 Aug 2004 → 29 Aug 2004

Publication series

Name	Proceedings of 2004 International Conference on Machine Learning and Cybernetics
Volume	4

Conference

Conference	Proceedings of 2004 International Conference on Machine Learning and Cybernetics
Country/Territory	China
City	Shanghai
Period	26/08/04 → 29/08/04

Keywords

Artificial intelligence
Chinese information processing
Natural language learning
Parsing

Cite this

@inproceedings{e45cafab29e84b629edad4806a9700a4,

title = "Parsing chinese with head-driven model",

abstract = "Great progress has been made in parsing the Wall Street Journal portion of the Penn Treebank. Now parsing languages other than English is an intensive research area. Head-driven model is one of the best English parsing models. It has been successfully applied to Czech but failed to outperform a baseline model in parsing German. This paper attempts to parse Chinese with head-driven model. Promising experimental results demonstrate that head-driven model works well for Chinese. We propose a hybrid parsing strategy, which combines head-driven model with a Chinese base phrases parsing model. The combined model not only improves the performance but also makes the parser space and time efficient. We evaluate our method in PARSEVAL measures, and the combined model performances are at 79.88\% precision, 81.97\% recall.",

keywords = "Artificial intelligence, Chinese information processing, Natural language learning, Parsing",

author = "Cao, \{Hai Long\} and Zhao, \{Tie Jun\} and Yang, \{Mu Yun\} and Sheng Li",

year = "2004",

language = "英语",

isbn = "0780384032",

series = "Proceedings of 2004 International Conference on Machine Learning and Cybernetics",

pages = "2618--2622",

booktitle = "Proceedings of 2004 International Conference on Machine Learning and Cybernetics",

note = "Proceedings of 2004 International Conference on Machine Learning and Cybernetics ; Conference date: 26-08-2004 Through 29-08-2004",

}

Cao, HL , Zhao, TJ , Yang, MY & Li, S 2004, Parsing chinese with head-driven model. in Proceedings of 2004 International Conference on Machine Learning and Cybernetics. Proceedings of 2004 International Conference on Machine Learning and Cybernetics, vol. 4, pp. 2618-2622, Proceedings of 2004 International Conference on Machine Learning and Cybernetics, Shanghai, China, 26/08/04.

Parsing chinese with head-driven model. / Cao, Hai Long ; Zhao, Tie Jun ; Yang, Mu Yun et al.
Proceedings of 2004 International Conference on Machine Learning and Cybernetics. 2004. p. 2618-2622 (Proceedings of 2004 International Conference on Machine Learning and Cybernetics; Vol. 4).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Parsing chinese with head-driven model

AU - Cao, Hai Long

AU - Zhao, Tie Jun

AU - Yang, Mu Yun

AU - Li, Sheng

PY - 2004

Y1 - 2004

N2 - Great progress has been made in parsing the Wall Street Journal portion of the Penn Treebank. Now parsing languages other than English is an intensive research area. Head-driven model is one of the best English parsing models. It has been successfully applied to Czech but failed to outperform a baseline model in parsing German. This paper attempts to parse Chinese with head-driven model. Promising experimental results demonstrate that head-driven model works well for Chinese. We propose a hybrid parsing strategy, which combines head-driven model with a Chinese base phrases parsing model. The combined model not only improves the performance but also makes the parser space and time efficient. We evaluate our method in PARSEVAL measures, and the combined model performances are at 79.88% precision, 81.97% recall.

AB - Great progress has been made in parsing the Wall Street Journal portion of the Penn Treebank. Now parsing languages other than English is an intensive research area. Head-driven model is one of the best English parsing models. It has been successfully applied to Czech but failed to outperform a baseline model in parsing German. This paper attempts to parse Chinese with head-driven model. Promising experimental results demonstrate that head-driven model works well for Chinese. We propose a hybrid parsing strategy, which combines head-driven model with a Chinese base phrases parsing model. The combined model not only improves the performance but also makes the parser space and time efficient. We evaluate our method in PARSEVAL measures, and the combined model performances are at 79.88% precision, 81.97% recall.

KW - Artificial intelligence

KW - Chinese information processing

KW - Natural language learning

KW - Parsing

UR - https://www.scopus.com/pages/publications/6344291724

M3 - 会议稿件

AN - SCOPUS:6344291724

SN - 0780384032

T3 - Proceedings of 2004 International Conference on Machine Learning and Cybernetics

SP - 2618

EP - 2622

BT - Proceedings of 2004 International Conference on Machine Learning and Cybernetics

T2 - Proceedings of 2004 International Conference on Machine Learning and Cybernetics

Y2 - 26 August 2004 through 29 August 2004

ER -

Parsing chinese with head-driven model

Abstract

Publication series

Conference

Keywords

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