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Using relation similarity on open information extraction-based event template extraction

机译:在基于开放信息提取的事件模板提取中使用关系相似性

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Automatic template extraction has been studied intensively in order to perform information extraction without predefined template. Several existing studies utilized the similar preprocessing techniques which are applied in Open Information Extraction (Open IE) paradigm system. We investigate the use of Open IE results to build the automatic event template extraction. In this study, we adapt the clustering based approach for template extraction, and propose to add the relation similarity information in the clustering function. We compare the clusters quality of the Open IE based system and non-Open IE based system and also with the use of relation similarity function using document classification metric. The experimental result shows that the performance of Open IE based system is comparable with the non-Open IE based system and the relation similarity information is able to improve the clusters quality.
机译:为了不使用预定义模板即可执行信息提取,已经对自动模板提取进行了深入研究。现有的一些研究利用了类似的预处理技术,这些技术已应用于开放信息提取(Open IE)范例系统中。我们调查了使用Open IE结果来构建自动事件模板提取的情况。在这项研究中,我们将基于聚类的方法用于模板提取,并建议在聚类功能中添加关系相似性信息。我们比较了基于Open IE的系统和非基于Open IE的系统的群集质量,还比较了使用基于文档分类度量的关系相似性功能的使用情况。实验结果表明,基于开放式IE的系统的性能与基于非开放式IE的系统相当,并且关系相似性信息可以提高集群的质量。

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