End-to-end neural relation extraction using deep biaffine attention

29 Dec 2018Dat Quoc NguyenKarin Verspoor

We propose a neural network model for joint extraction of named entities and relations between them, without any hand-crafted features. The key contribution of our model is to extend a BiLSTM-CRF-based entity recognition model with a deep biaffine attention layer to model second-order interactions between latent features for relation classification, specifically attending to the role of an entity in a directional relationship... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT LEADERBOARD
Relation Extraction CoNLL04 Biaffine attention Entity F1 86.20 # 3
Relation F1 64.4 # 2
Relation F1 64.40 # 4