With the accelerating growth of big data, especially in the healthcare area, information extraction is more needed currently than ever, for it can convey unstructured information into an easily interpretable structured data. Relation extraction is the second of the two important tasks of relation extraction. This study presents an overview of relation extraction using distant supervision, providing a generalized architecture of this task based on the state-of-the-art work that proposed this method. Besides, it surveys the methods used in the literature targeting this topic with a description of different knowledge bases used in the process along with the corpora, which can be helpful for beginner practitioners seeking knowledge on this subject. Moreover, the limitations of the proposed approaches and future challenges were highlighted, and possible solutions were proposed.

中文翻译：

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使用远程监督的生物医学关系提取

随着大数据的加速增长，尤其是在医疗保健领域，当前比以往任何时候都更需要信息提取，因为它可以将非结构化信息转化为易于解释的结构化数据。关系抽取是关系抽取的两个重要任务中的第二个。本研究概述了使用远程监督的关系提取，并基于提出此方法的最新工作提供了该任务的通用架构。此外，它还调查了针对该主题的文献中使用的方法，并描述了该过程中使用的不同知识库以及语料库，这有助于初学者寻求有关该主题的知识。此外，还强调了拟议方法的局限性和未来的挑战，