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Joint Extraction of Compound Entities and Relationships from Biomedical Literature

机译:从生物医学文献的复合实体和关系的联合提取

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In this paper we identify some limitations of contemporary information extraction mechanisms in the context of biomedical literature. We present an extraction mechanism that generates structured representations of textual content. Our extraction mechanism achieves this by extracting compound entities, and relationships between them, occuring in text. A detailed evaluation of the relationship and compound entities extracted is presented. Our results show over 62% average precision across 8 relationship types tested with over 82% average precision for compound entity identification.
机译:在本文中,我们在生物医学文献背景下确定了当代信息提取机制的一些局限性。我们提出了一种提取机制,可以产生构成的文本内容的表示。我们的提取机制通过提取复合实体和它们之间的关系来实现这一点。提出了提取的关系和化合物实体的详细评价。我们的结果显示超过8个关系类型的平均精度超过82%,用于复合实体识别超过82%的平均精度。

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