NCUEE-NLP at SemEval-2023 Task 7: Ensemble Biomedical LinkBERT Transformers in Multi-evidence Natural Language Inference for Clinical Trial Data

Chao Yi Chen, Kao Yuan Tien, Yuan Hao Cheng, Lung Hao Lee

研究成果: 書貢獻/報告類型會議論文篇章同行評審

1 引文 斯高帕斯(Scopus)

摘要

This study describes the model design of the NCUEE-NLP system for the SemEval-2023 NLI4CT task that focuses on multi-evidence natural language inference for clinical trial data. We use the LinkBERT transformer in the biomedical domain (denoted as BioLinkBERT) as our main system architecture. First, a set of sentences in clinical trial reports is extracted as evidence for premise-statement inference. This identified evidence is then used to determine the inference relation (i.e., entailment or contradiction). Finally, a soft voting ensemble mechanism is applied to enhance the system performance. For Subtask 1 on textual entailment, our best submission had an F1-score of 0.7091, ranking sixth among all 30 participating teams. For Subtask 2 on evidence retrieval, our best result obtained an F1-score of 0.7940, ranking ninth of 19 submissions.

原文???core.languages.en_GB???
主出版物標題17th International Workshop on Semantic Evaluation, SemEval 2023 - Proceedings of the Workshop
編輯Atul Kr. Ojha, A. Seza Dogruoz, Giovanni Da San Martino, Harish Tayyar Madabushi, Ritesh Kumar, Elisa Sartori
發行者Association for Computational Linguistics
頁面776-781
頁數6
ISBN(電子)9781959429999
出版狀態已出版 - 2023
事件17th International Workshop on Semantic Evaluation, SemEval 2023, co-located with the 61st Annual Meeting of the Association for Computational Linguistics, ACL 2023 - Hybrid, Toronto, Canada
持續時間: 13 7月 202314 7月 2023

出版系列

名字17th International Workshop on Semantic Evaluation, SemEval 2023 - Proceedings of the Workshop

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???event.eventtypes.event.conference???17th International Workshop on Semantic Evaluation, SemEval 2023, co-located with the 61st Annual Meeting of the Association for Computational Linguistics, ACL 2023
國家/地區Canada
城市Hybrid, Toronto
期間13/07/2314/07/23

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