Definition Extraction systems are a valuable knowledge source for both humans and algorithms.
Representations in the hidden layers of Deep Neural Networks (DNN) are often hard to interpret since it is difficult to project them into an interpretable domain.
Distantly supervised relation extraction is widely used to extract relational facts from text, but suffers from noisy labels.
Unlike previous relation extraction models, TRE uses pre-trained deep language representations instead of explicit linguistic features to inform the relation classification and combines it with the self-attentive Transformer architecture to effectively model long-range dependencies between entity mentions.
Ranked #13 on Relation Extraction on SemEval-2010 Task 8