A maximum entropy approach to HowNet-based Chinese word sense disambiguation

Authors:
Wong Ping Wai;Yang Yongsheng
Affiliations:
Intendi Inc., Clear Water Bay, Hong Kong;HKUST, Clear Water Bay, Hong Kong
Venue:
SEMANET '02 Proceedings of the 2002 workshop on Building and using semantic networks - Volume 11
Year:
2002

Citing 2
Cited 1

The research of word sense disambiguation method based on co-occurrence frequency of Hownet

CLPW '00 Proceedings of the second workshop on Chinese language processing: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 12
Annotating information structures in Chinese texts using HowNet

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Word sense disambiguation through sememe labeling

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Abstract

This paper presents a maximum entropy method for the disambiguation of word senses as defined in HowNet. With the release of this bilingual (Chinese and English) knowledge base in 1999, a corpus of 30,000 words was sense tagged and released in January 2002. Concepts meanings in HowNet are constructed by a closed set of sememes, the smallest meaning units, which can be treated as semantic tags. The maximum entropy model treats semantic tags like parts-of-speech tags and achieves an overall accuracy of 89.39%, outperforming a baseline system, which picks the most frequent sense.