Relation extraction from text is an important task for automatic knowledge base population. In this thesis, we first propose a syntax-focused multi-factor attention network model for finding the relation between two entities. Next, we propose two joint entity and relation extraction frameworks based on encoder-decoder architecture. Finally, we propose a hierarchical entity graph convolutional network for relation extraction across documents.
翻译:从文本中提取关系对于自动知识基础群来说是一项重要任务。 在这个论文中,我们首先提出一个注重语法的多要素关注网络模式,以寻找两个实体之间的关系。接下来,我们提出两个基于编码器-解码器结构的联合实体和关系提取框架。最后,我们建议建立一个分级实体图形共进网络,以便在文件之间提取关系。