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- W4385571821 abstract "Clinical Trials Reports (CTRs) contain highly valuable health information from which Natural Language Inference (NLI) techniques determine if a given hypothesis can be inferred from a given premise. CTRs are abundant with domain terminology with particular terms that are difficult to understand without prior knowledge. Thus, we proposed to use domain ontologies as a source of external knowledge that could help with the inference process in theSemEval-2023 Task 7: Multi-evidence Natural Language Inference for Clinical Trial Data (NLI4CT). This document describes our participation in subtask 1: Textual Entailment, where Ontologies, NLP techniques, such as tokenization and named-entity recognition, and rule-based approaches are all combined in our approach. We were able to show that inputting annotations from domain ontologies improved the baseline systems." @default.
- W4385571821 created "2023-08-05" @default.
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- W4385571821 date "2023-01-01" @default.
- W4385571821 modified "2023-09-24" @default.
- W4385571821 title "lasigeBioTM at SemEval-2023 Task 7: Improving Natural Language Inference Baseline Systems with Domain Ontologies" @default.
- W4385571821 doi "https://doi.org/10.18653/v1/2023.semeval-1.2" @default.
- W4385571821 hasPublicationYear "2023" @default.
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