HIT-IR-WSD: A WSD system for English lexical sample task

Yuhang Guo; Wanxiang Che; Yuxuan Hu; Wei Zhang; Ting Liu

HIT-IR-WSD: A WSD system for English lexical sample task

Yuhang Guo
, Wanxiang Che
, Yuxuan Hu
, Wei Zhang
, Ting Liu

Harbin Institute of Technology

Research output: Contribution to conference › Paper › peer-review

8 Citations (Scopus)

Abstract

HIT-IR-WSD is a word sense disambiguation (WSD) system developed for English lexical sample task (Task 11) of Semeval 2007 by Information Retrieval Lab, Harbin Institute of Technology. The system is based on a supervised method using an SVM classifier. Multi-resources including words in the surrounding context, the partof-speech of neighboring words, collocations and syntactic relations are used. The final micro-avg raw score achieves 81.9% on the test set, the best one among participating runs.

Original language	English
Pages	165-168
Number of pages	4
Publication status	Published - 2007
Externally published	Yes
Event	4th International Workshop on Semantic Evaluations, SemEval 2007 in conjunction with the Association for Computational Linguistics, ACL 2007 - Prague, Czech Republic Duration: 23 Jun 2007 → 24 Jun 2007

Conference

Conference	4th International Workshop on Semantic Evaluations, SemEval 2007 in conjunction with the Association for Computational Linguistics, ACL 2007
Country/Territory	Czech Republic
City	Prague
Period	23/06/07 → 24/06/07

Cite this

@conference{d45aa2a92dd243aba786b15b77cbf119,

title = "HIT-IR-WSD: A WSD system for English lexical sample task",

abstract = "HIT-IR-WSD is a word sense disambiguation (WSD) system developed for English lexical sample task (Task 11) of Semeval 2007 by Information Retrieval Lab, Harbin Institute of Technology. The system is based on a supervised method using an SVM classifier. Multi-resources including words in the surrounding context, the partof-speech of neighboring words, collocations and syntactic relations are used. The final micro-avg raw score achieves 81.9\% on the test set, the best one among participating runs.",

author = "Yuhang Guo and Wanxiang Che and Yuxuan Hu and Wei Zhang and Ting Liu",

note = "Publisher Copyright: {\textcopyright} 2007 Association for Computational Linguistics.; 4th International Workshop on Semantic Evaluations, SemEval 2007 in conjunction with the Association for Computational Linguistics, ACL 2007 ; Conference date: 23-06-2007 Through 24-06-2007",

year = "2007",

language = "English",

pages = "165--168",

}

HIT-IR-WSD: A WSD system for English lexical sample task. / Guo, Yuhang; Che, Wanxiang; Hu, Yuxuan et al.
2007. 165-168 Paper presented at 4th International Workshop on Semantic Evaluations, SemEval 2007 in conjunction with the Association for Computational Linguistics, ACL 2007, Prague, Czech Republic.

Research output: Contribution to conference › Paper › peer-review

TY - CONF

T1 - HIT-IR-WSD

T2 - 4th International Workshop on Semantic Evaluations, SemEval 2007 in conjunction with the Association for Computational Linguistics, ACL 2007

AU - Guo, Yuhang

AU - Che, Wanxiang

AU - Hu, Yuxuan

AU - Zhang, Wei

AU - Liu, Ting

PY - 2007

Y1 - 2007

N2 - HIT-IR-WSD is a word sense disambiguation (WSD) system developed for English lexical sample task (Task 11) of Semeval 2007 by Information Retrieval Lab, Harbin Institute of Technology. The system is based on a supervised method using an SVM classifier. Multi-resources including words in the surrounding context, the partof-speech of neighboring words, collocations and syntactic relations are used. The final micro-avg raw score achieves 81.9% on the test set, the best one among participating runs.

AB - HIT-IR-WSD is a word sense disambiguation (WSD) system developed for English lexical sample task (Task 11) of Semeval 2007 by Information Retrieval Lab, Harbin Institute of Technology. The system is based on a supervised method using an SVM classifier. Multi-resources including words in the surrounding context, the partof-speech of neighboring words, collocations and syntactic relations are used. The final micro-avg raw score achieves 81.9% on the test set, the best one among participating runs.

UR - https://www.scopus.com/pages/publications/84968739205

M3 - Paper

AN - SCOPUS:84968739205

SP - 165

EP - 168

Y2 - 23 June 2007 through 24 June 2007

ER -

HIT-IR-WSD: A WSD system for English lexical sample task

Abstract

Conference

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