Word sense disambiguation of adjectives using dependency structure and degree of association between sentences

Kenichi Mishina, S. Tsuchiya, H. Watabe
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引用次数: 4

Abstract

Good WSD results has been shown by the supervised methods. But it is extremely costly to manually construct a corpus with semantic label as learning data. It is not for practical use. Therefore, the unsupervised methods using dictionary knowledge have been actively researched. Many conventional unsupervised WSD is using English dictionary. There are few cases of unsupervised WSD in Japanese. Therefore it is necessary to improve the accuracy of unsupervised WSD. In this paper, we propose a new unsupervised WSD method of adjectives using sentence structure information and dictionary knowledge. As the evaluation result, the accuracy was 29.1% in the conventional method, and it was 40.2% in the proposed method. Calculation of the z-test confirmed that the evaluation result was significant.
利用句子间的依存结构和关联度进行形容词词义消歧
有监督的方法取得了良好的水处理效果。但人工构建一个以语义标签作为学习数据的语料库是非常昂贵的。这不是为了实际用途。因此,利用字典知识的无监督方法得到了积极的研究。许多传统的无监督水务署使用的是英语词典。日本很少有无人监管的水务署。因此,有必要提高无监督WSD的准确性。本文利用句子结构信息和词典知识,提出了一种新的形容词无监督WSD方法。评价结果表明,传统方法的准确率为29.1%,所提方法的准确率为40.2%。z检验计算证实评价结果显著。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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