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2022 COLING COLING 2022

CLaCLab at SocialDisNER: Using Medical Gazetteers for Named-Entity Recognition of Disease Mentions in Spanish Tweets

Abstract

AbstractThis paper summarizes the CLaC submission for SMM4H 2022 Task 10 which concerns the recognition of diseases mentioned in Spanish tweets. Before classifying each token, we encode each token with a transformer encoder using features from Multilingual RoBERTa Large, UMLS gazetteer, and DISTEMIST gazetteer, among others. We obtain a strict F1 score of 0.869, with competition mean of 0.675, standard deviation of 0.245, and median of 0.761.

Authors

Harsh Verma, Parsa Bagherzadeh, Sabine Bergler

Topics

Machine Learning > Core Methods > Classification

Keywords

named entity recognition transformer encoder multilingual roberta disease mention spanish tweet medical gazetteer
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