Task-oriented Evaluation of Syntactic Parsers and Their Representations
Task-oriented Evaluation of Syntactic Parsers and Their Representations
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发表时间：
2008-06
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通讯作者：
Yusuke Miyao;Rune Sætre;Kenji Sagae;Takuya Matsuzaki;Junichi Tsujii
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作者：
Yusuke Miyao;Rune Sætre;Kenji Sagae;Takuya Matsuzaki;Junichi Tsujii
本文对几种基于不同框架的英语句法分析器进行了比较评价。我们的方法是测量每个解析器作为生物医学论文中执行蛋白质-蛋白质相互作用(PPI)识别的信息提取系统的组件时的影响。我们使用五种不同的句法表示对八种句法分析器(基于依存句法分析、短语结构句法分析或深度句法分析)进行了评估。我们运行了一个PPI系统，使用了几种解析器和解析表示的组合，并检查了它们对PPI识别精度的影响。我们的实验表明，用这些不同的解析器获得的准确率水平是相似的，但当用特定于领域的数据重新训练解析器时，准确率的提高会有所不同。
This paper presents a comparative evaluation of several state-of-the-art English parsers based on different frameworks. Our approach is to measure the impact of each parser when it is used as a component of an information extraction system that performs protein-protein interaction (PPI) identification in biomedical papers. We evaluate eight parsers (based on dependency parsing, phrase structure parsing, or deep parsing) using five different parse representations. We run a PPI system with several combinations of parser and parse representation, and examine their impact on PPI identification accuracy. Our experiments show that the levels of accuracy obtained with these different parsers are similar, but that accuracy improvements vary when the parsers are retrained with domain-specific data.