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Syntactic features for high precision Word Sense Disambiguation

机译:高精度词义消歧的句法功能

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摘要

This paper explores the contribution of a broad range of syntactic features to WSD: grammatical relations coded as the presence of adjuncts/arguments in isolation or as subcategorization frames, and instantiated grammatical relations between words. We have tested the performance of syntactic features using two different ML algorithms (Decision Lists and AdaBoost) on the Senseval-2 data. Adding syntactic features to a basic set of traditional features improves performance, especially for AdaBoost. In addition, several methods to build arbitrarily high accuracy WSD systems are also tried, showing that syntactic features allow for a precision of 86% and a coverage of 26% or 95% precision and 8% coverage.
机译:本文探讨了广泛的句法特征对WSD的贡献:语法关系编码为孤立存在的辅助词/自变量或子分类框架,以及单词之间的实例化语法关系。我们已经使用两种不同的ML算法(决策列表和AdaBoost)对Senseval-2数据测试了语法功能的性能。在一组基本的传统功能中添加语法功能可以提高性能,尤其是对于AdaBoost。此外,还尝试了几种构建任意高精度WSD系统的方法,这些方法表明语法功能可实现86%的精度和26%的覆盖率,或者95%的精度和8%的覆盖率。

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