Attention Based Bidirectional Long Short Term Memory Networks for Relation Classification
Relation classification is an important semantic processing task in the field of natural language processing (NLP) State ofthe art systems still rely on lexical resources such as WordNet or NLP systems like dependency parser and named entity recognizers (NER) to get high level features. Another challenge is that important information can appear at any position in the sentence. To tackle these problems, we propose Attention Based Bidirectional Long Short Term Memory Networks(AttBLSTM) to capture the most important semantic information in a sentence. The experimental results on the SemEval 2010 relation classification task show that our method outperforms most of the existing methods, with only word vectors.
ACL