首页> 外文期刊>International journal of medical informatics >Evaluation of two dependency parsers on biomedical corpus targeted at protein—protein interactions
【24h】

Evaluation of two dependency parsers on biomedical corpus targeted at protein—protein interactions

机译:针对针对蛋白质-蛋白质相互作用的生物医学语料库的两个依赖性解析器的评估

获取原文
获取原文并翻译 | 示例
           

摘要

We present an evaluation of Link Grammar and Connexor Machinese Syntax, two major broad-coverage dependency parsers, on a custom hand-annotated corpus consisting of sentences regarding protein—protein interactions. In the evaluation, we apply the notion of an interaction subgraph, which is the subgraph of a dependency graph expressing a protein-protein interaction. We measure the performance of the parsers for recovery of individual dependencies, fully correct parses, and interaction subgraphs. For Link Grammar, an open system that can be inspected in detail, we further perform a comprehensive failure analysis, report specific causes of error, and suggest potential modifications to the grammar. We find that both parsers perform worse on biomedical English than previously reported on general English. While Connexor Machinese Syntax significantly outperforms Link Grammar, the failure analysis suggests specific ways in which the latter could be modified for better performance in the domain.
机译:我们在一个自定义的手工标注语料库上对链接语法和Connexor Machinese语法(两个主要的广泛覆盖的依赖分析器)进行了评估,该语料库由有关蛋白质-蛋白质相互作用的句子组成。在评估中,我们应用了交互子图的概念,该子图是表示蛋白质-蛋白质交互作用的依赖图的子图。我们测量解析器的性能,以恢复单个依赖项,完全正确的解析和交互子图。对于可以详细检查的开放系统链接语法,我们将进一步进行全面的故障分析,报告错误的具体原因,并提出对语法的潜在修改建议。我们发现,两个解析器在生物医学英语上的表现都比以前在通用英语上报告的要差。尽管Connexor Machinese语法的性能明显优于Link Grammar,但故障分析提出了可以修改后者以在域中实现更好性能的特定方法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号