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    <abstract>Recently BERT has achieved a state-of-the-art 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.</abstract>
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%0 Conference Proceedings
%T A BERT-based One-Pass Multi-Task Model for Clinical Temporal Relation Extraction
%A Lin, Chen
%A Miller, Timothy
%A Dligach, Dmitriy
%A Sadeque, Farig
%A Bethard, Steven
%A Savova, Guergana
%Y Demner-Fushman, Dina
%Y Cohen, Kevin Bretonnel
%Y Ananiadou, Sophia
%Y Tsujii, Junichi
%S Proceedings of the 19th SIGBioMed Workshop on Biomedical Language Processing
%D 2020
%8 July
%I Association for Computational Linguistics
%C Online
%F lin-etal-2020-bert
%X Recently BERT has achieved a state-of-the-art 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.
%R 10.18653/v1/2020.bionlp-1.7
%U https://aclanthology.org/2020.bionlp-1.7
%U https://doi.org/10.18653/v1/2020.bionlp-1.7
%P 70-75

Markdown (Informal)

[A BERT-based One-Pass Multi-Task Model for Clinical Temporal Relation Extraction](https://aclanthology.org/2020.bionlp-1.7) (Lin et al., BioNLP 2020)

• A BERT-based One-Pass Multi-Task Model for Clinical Temporal Relation Extraction (Lin et al., BioNLP 2020)

ACL

• Chen Lin, Timothy Miller, Dmitriy Dligach, Farig Sadeque, Steven Bethard, and Guergana Savova. 2020. A BERT-based One-Pass Multi-Task Model for Clinical Temporal Relation Extraction. In Proceedings of the 19th SIGBioMed Workshop on Biomedical Language Processing, pages 70–75, Online. Association for Computational Linguistics.