SemEval-2023 Task 7: Multi-Evidence Natural Language Inference for Clinical Trial Data
Maël Jullien, Marco Valentino, Hannah Frost, Paul O’Regan, Dónal Landers, André Azul Freitas · 2023
This paper describes the results of Se-mEval 2023 task 7 -Multi-Evidence Natural Language Inference for Clinical Trial Data (NLI4CT) -consisting of 2 tasks, a Natural Language Inference (NLI) task, and an evidence selection task on clinical trial data.The proposed challenges require multi-hop biomedical and numerical reasoning, which are of significant importance to the development of systems capable of large-scale interpretation and retrieval of medical evidence, to provide personalized evidence-based care.We envisage that the dataset, models, and results of this task will be useful to the biomedical NLI and evidence retrieval communities.The dataset 1 , competition leaderboard 2 , and website 3 are publicly available.