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Unsupervised Translation Disambiguation Based on Equivalent PseudoTranslation Model |
Liu Peng-yuan; Zhao Tie-jun; Yang Mu-yun; Li Zhuang |
MOE-MS Key Laboratory of Natural Language Processing and Speech, Harbin Institute of Technology, Harbin 150001, China |
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Abstract This paper describes an unsupervised translation disambiguation method based on the Equivalent Pseudo Translation (EPT). EPT is constructed by using non-ambiguous words of target language, which is semantically equivalent to the source ambiguous words. Sense-tagged examples are automatically extracted from a large scale Chinese corpus, by which a semantic classifier of EPT is formed. In order to apply the EPT classifier, English examples are mapped into a set of Chinese words by Hownet. This method is evaluated on the Senseval-2 framework of English lexical sample task, achieving the top performance against all other previous works which extract sense-tagged examples automatically. The results are very close to the state-of-the-art comparable unsupervised systems.
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Received: 25 June 2007
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