CLinkaRT at EVALITA 2023: Overview of the Task on Linking a Lab Result to its Test Event in the Clinical Domain

CLinkaRT at EVALITA 2023 is a relation extraction task based on clinical cases taken from the E3C corpus, i.e. Italian written documents reporting statements of a clinical practice. The task consists in identifying clinical results and measures and linking them to the laboratory tests and measurements from which they were obtained. Three teams participated in the task and various supervised machine learning models, both traditional and based on deep learning, were evaluated. In this evaluation, the deep learning models outperformed the traditional ones. Interestingly, none of the teams explored the use of few-shot language modeling. However, the fact that the supervised models significantly outperformed the task baselines implementing few-shot learning shows the crucial role still played by the availability of annotated training data.