A BERT-based One-Pass Multi-Task Model for Clinical Temporal Relation Extraction
Chen Lin, Timothy Miller, Dmitriy Dligach, Farig Sadeque, Steven J. Bethard, Guergana Savova · 2020
Recently BERT has achieved a state-of-theart performance in temporal relation extraction from clinical Electronic Medical Records text.However, the current approach is inefficient as it requires multiple passes through each input sequence.We extend a recently-proposed one-pass model for relation classification to a one-pass model for relation extraction.We augment this framework by introducing global embeddings to help with long-distance relation inference, and by multi-task learning to increase model performance and generalizability.Our proposed model produces results on par with the state-of-the-art in temporal relation extraction on the THYME corpus and is much "greener" in computational cost.