ITTC at SemEval 2023-Task 7: Document Retrieval and Sentence Similarity for Evidence Retrieval in Clinical Trial Data
Rahmad Mahendra, Damiano Spina, Karin Verspoor
The 17th International Workshop on Semantic Evaluation (SemEval-2023) Task 7: multi-evidence natural language inference for clinical trial data Paper
TLDR:
This paper describes the submissions of the Natural Language Processing (NLP) team from the Australian Research Council Industrial Transformation Training Centre (ITTC) for Cognitive Computing in Medical Technologies to the SemEval 2023 Task 7, i.e., multi-evidence natural language inference for cli
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Abstract:
This paper describes the submissions of the Natural Language Processing (NLP) team from the Australian Research Council Industrial Transformation Training Centre (ITTC) for Cognitive Computing in Medical Technologies to the SemEval 2023 Task 7, i.e., multi-evidence natural language inference for clinical trial data (NLI4CT). More specifically, we were working on subtask 2 whose objective is to identify the relevant parts of the premise from clinical trial report that justify the truth of information in the statement. We approach the evidence retrieval problem as a document retrieval and sentence similarity task. Our results show that the task poses some challenges which involve dealing with complex sentences and implicit evidences.