[ACL2016]Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classification
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关系分类在自然语言处理领域是一个很重要的语义处理任务，目前state-of-the-art system非常依赖于lexical resources 比如WordNet或者dependency parser 和NER. 还有一个挑战是重要信息不知道在句中的什么位置。鉴于此，本文提出了Attention-based bidirectional long short-term memory networks(att-BLSTM)用于capture 句中的重要信息。
特别注意的是：本文model没用使用any features derived from lexical resources or NLP system
这个链接给出了神经网络应用与关系抽取的诸多介绍：
http://blog.csdn.net/sparkexpert/article/details/72785304
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