Abstract
This paper describes a system developed for the Social Media Mining for Health (SMM4H) 2019 shared tasks. Specifically, we participated in three tasks. The goals of the first two tasks are to classify whether a tweet contains mentions of adverse drug reactions (ADR) and extract these mentions, respectively. The objective of the third task is to build an end-to-end solution: first, detect ADR mentions and then map these entities to concepts in a controlled vocabulary. We investigate the use of a language representation model BERT trained to obtain semantic representations of social media texts. Our experiments on a dataset of user reviews showed that BERT is superior to state-of-the-art models based on recurrent neural networks. The BERT-based system for Task 1 obtained an F1 of 57.38%, with improvements up to +7.19% F1 over a score averaged across all 43 submissions. The ensemble of neural networks with a voting scheme for named entity recognition ranked first among 9 teams at the SMM4H 2019 Task 2 and obtained a relaxed F1 of 65.8%. The end-to-end model based on BERT for ADR normalization ranked first at the SMM4H 2019 Task 3 and obtained a relaxed F1 of 43.2%.- Anthology ID:
- W19-3207
- Volume:
- Proceedings of the Fourth Social Media Mining for Health Applications (#SMM4H) Workshop & Shared Task
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Davy Weissenbacher, Graciela Gonzalez-Hernandez
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 52–57
- Language:
- URL:
- https://aclanthology.org/W19-3207
- DOI:
- 10.18653/v1/W19-3207
- Cite (ACL):
- Zulfat Miftahutdinov, Ilseyar Alimova, and Elena Tutubalina. 2019. KFU NLP Team at SMM4H 2019 Tasks: Want to Extract Adverse Drugs Reactions from Tweets? BERT to The Rescue. In Proceedings of the Fourth Social Media Mining for Health Applications (#SMM4H) Workshop & Shared Task, pages 52–57, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- KFU NLP Team at SMM4H 2019 Tasks: Want to Extract Adverse Drugs Reactions from Tweets? BERT to The Rescue (Miftahutdinov et al., ACL 2019)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/W19-3207.pdf
- Data
- SMM4H