Coordinate Noun Phrase Disambiguation in a Generative Parsing Model
Coordinate Noun Phrase Disambiguation in a Generative Parsing Model
复制标题
生成解析模型中的协调名词短语消歧
DOI：
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发表时间：
2007
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通讯作者：
Deirdre Hogan
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文献类型：
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作者：
Deirdre Hogan
在本文中，我们提出了一个词汇化的历史为基础的分析模型的框架内，提高名词短语（NP）协调消歧的方法。除了减少数据中的噪音，我们还研究了消除歧义的两个主要信息来源：合取结构的对称性和合取词头之间的依赖性。我们对基线模型的改变导致NP协调依赖性f分数从69.9%增加到73.8%，这表示f分数误差相对减少了13%。
In this paper we present methods for improving the disambiguation of noun phrase (NP) coordination within the framework of a lexicalised history-based parsing model. As well as reducing noise in the data, we look at modelling two main sources of information for disambiguation: symmetry in conjunct structure, and the dependency between conjunct lexical heads. Our changes to the baseline model result in an increase in NP coordination dependency f-score from 69.9% to 73.8%, which represents a relative reduction in f-score error of 13%.