[EMNLP2015]Distant supervision for Relation Extraction via Piecewise Convolutional Neural Networks
2018-01-04 10:02
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paper中提高两个概念：
(1)distant supervision: 如果两个实体在已知知识库中有关系，则包含这两个实体的中，两个实体的的关系默认就是知识库中给定的关系, 因为人工标注语料代价大，所以一般用distant supervision标注语料
(2)multi-instance learning:训练语料是很多带有正负标签的包，每个包里有很多示例，如果一个包里包含至少一个示例是正标签则这个包就标记为正，如果一个包里的示例都是负的，则该包的标签就是负的，包里具体的示例是什么标签并不明确，能确定的就是包的标签，在测试语料中，我们的目的是给包打标签
(1)distant supervision: 如果两个实体在已知知识库中有关系，则包含这两个实体的中，两个实体的的关系默认就是知识库中给定的关系, 因为人工标注语料代价大，所以一般用distant supervision标注语料
(2)multi-instance learning:训练语料是很多带有正负标签的包，每个包里有很多示例，如果一个包里包含至少一个示例是正标签则这个包就标记为正，如果一个包里的示例都是负的，则该包的标签就是负的，包里具体的示例是什么标签并不明确，能确定的就是包的标签，在测试语料中，我们的目的是给包打标签
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