Matching the Blanks: Distributional Similarity for Relation Learning论文笔记
动机 本文主要在于设计一个通用的关系抽取器，即学到一个合适的关系的表达，可以对任意关系建模。之前的工作，如利用Surface Form来表示关系，或者借助知识库中关系的定义，但这两类方案都需要事先定义好关系，泛化能力较弱。 本文受到word2vec中的分布式假设（Harris’ distributional hypothesis）的启发，想利用上下文将关系编码成一个固定长度的向量。这就将关系抽取的
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相关文章
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