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An Evidence-Based Verification Approach to Extract Entities and Relations for Knowledge Base Population

机译:提取知识库人口的实体和关系的基于证据的核查方法

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This paper presents an approach to automatically extract entities and relationships from textual documents. The main goal is to populate a knowledge base that hosts this structured information about domain entities. The extracted entities and their expected relationships are verified using two evidence based techniques: classification and linking. This last process also enables the linking of our knowledge base to other sources which are part of the Linked Open Data cloud. We demonstrate the benefit of our approach through series of experiments with real-world datasets.
机译:本文介绍了自动从文本文档中提取实体和关系的方法。主要目标是填充托管有关域实体的结构化信息的知识库。使用两种基于证据的技术来验证提取的实体及其预期关系:分类和链接。最后一个进程还可以将我们的知识库链接到作为链接开放数据云的一部分的其他来源。我们通过具有现实世界数据集的一系列实验展示了我们方法的好处。

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