@inproceedings{vassileva-etal-2023-fmi,
title = "{FMI}-{SU} at {S}em{E}val-2023 Task 7: Two-level Entailment Classification of Clinical Trials Enhanced by Contextual Data Augmentation",
author = "Vassileva, Sylvia and
Grazhdanski, Georgi and
Boytcheva, Svetla and
Koychev, Ivan",
editor = {Ojha, Atul Kr. and
Do{\u{g}}ru{\"o}z, A. Seza and
Da San Martino, Giovanni and
Tayyar Madabushi, Harish and
Kumar, Ritesh and
Sartori, Elisa},
booktitle = "Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.semeval-1.200",
doi = "10.18653/v1/2023.semeval-1.200",
pages = "1454--1462",
abstract = "The paper presents an approach for solving SemEval 2023 Task 7 - identifying the inference relation in a clinical trials dataset. The system has two levels for retrieving relevant clinical trial evidence for a statement and then classifying the inference relation based on the relevant sentences. In the first level, the system classifies the evidence-statement pairs as relevant or not using a BERT-based classifier and contextual data augmentation (subtask 2). Using the relevant parts of the clinical trial from the first level, the system uses an additional BERT-based classifier to determine whether the relation is entailment or contradiction (subtask 1). In both levels, the contextual data augmentation is showing a significant improvement in the F1 score on the test set of 3.7{\%} for subtask 2 and 7.6{\%} for subtask 1, achieving final F1 scores of 82.7{\%} for subtask 2 and 64.4{\%} for subtask 1.",
}
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<abstract>The paper presents an approach for solving SemEval 2023 Task 7 - identifying the inference relation in a clinical trials dataset. The system has two levels for retrieving relevant clinical trial evidence for a statement and then classifying the inference relation based on the relevant sentences. In the first level, the system classifies the evidence-statement pairs as relevant or not using a BERT-based classifier and contextual data augmentation (subtask 2). Using the relevant parts of the clinical trial from the first level, the system uses an additional BERT-based classifier to determine whether the relation is entailment or contradiction (subtask 1). In both levels, the contextual data augmentation is showing a significant improvement in the F1 score on the test set of 3.7% for subtask 2 and 7.6% for subtask 1, achieving final F1 scores of 82.7% for subtask 2 and 64.4% for subtask 1.</abstract>
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%0 Conference Proceedings
%T FMI-SU at SemEval-2023 Task 7: Two-level Entailment Classification of Clinical Trials Enhanced by Contextual Data Augmentation
%A Vassileva, Sylvia
%A Grazhdanski, Georgi
%A Boytcheva, Svetla
%A Koychev, Ivan
%Y Ojha, Atul Kr.
%Y Doğruöz, A. Seza
%Y Da San Martino, Giovanni
%Y Tayyar Madabushi, Harish
%Y Kumar, Ritesh
%Y Sartori, Elisa
%S Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F vassileva-etal-2023-fmi
%X The paper presents an approach for solving SemEval 2023 Task 7 - identifying the inference relation in a clinical trials dataset. The system has two levels for retrieving relevant clinical trial evidence for a statement and then classifying the inference relation based on the relevant sentences. In the first level, the system classifies the evidence-statement pairs as relevant or not using a BERT-based classifier and contextual data augmentation (subtask 2). Using the relevant parts of the clinical trial from the first level, the system uses an additional BERT-based classifier to determine whether the relation is entailment or contradiction (subtask 1). In both levels, the contextual data augmentation is showing a significant improvement in the F1 score on the test set of 3.7% for subtask 2 and 7.6% for subtask 1, achieving final F1 scores of 82.7% for subtask 2 and 64.4% for subtask 1.
%R 10.18653/v1/2023.semeval-1.200
%U https://aclanthology.org/2023.semeval-1.200
%U https://doi.org/10.18653/v1/2023.semeval-1.200
%P 1454-1462
Markdown (Informal)
[FMI-SU at SemEval-2023 Task 7: Two-level Entailment Classification of Clinical Trials Enhanced by Contextual Data Augmentation](https://aclanthology.org/2023.semeval-1.200) (Vassileva et al., SemEval 2023)
ACL