高精度词义消歧的句法特征

David Martínez, Eneko Agirre, Lluís Màrquez i Villodre
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引用次数: 38

摘要

本文探讨了广泛的语法特征对WSD的贡献:编码为孤立的辅词/参数或子分类框架的语法关系,以及单词之间的实例化语法关系。我们在Senseval-2数据上使用两种不同的ML算法(Decision Lists和AdaBoost)测试了语法特征的性能。在一组基本的传统特性中添加语法特性可以提高性能,特别是对于AdaBoost。此外,还尝试了几种构建任意高精度WSD系统的方法,结果表明,语法特征允许86%的精度和26%的覆盖率或95%的精度和8%的覆盖率。
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Syntactic Features for High Precision Word Sense Disambiguation
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.
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