TermEval 2020 : shared task on automatic term extraction using the Annotated Corpora for term Extraction Research (ACTER) dataset

Publication type
C1
Publication status
Published
Authors
Rigouts Terryn, A., Hoste, V., Drouin, P., & Lefever, E.
Editor
BĂ©atrice Daile, Kyo Kageura and Ayla Rigouts Terryn
Series
6th International Workshop on Computational Terminology (COMPUTERM 2020), Proceedings
Pagination
85-94
Publisher
European Language Resources Association (ELRA)
Conference
6th International Workshop on Computational Terminology (COMPUTERM 2020) (Marsaille, france)
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Abstract

The TermEval 2020 shared task provided a platform for researchers to work on automatic term extraction (ATE) with the same dataset: the Annotated Corpora for Term Extraction Research (ACTER). The dataset covers three languages (English, French, and Dutch) and four domains, of which the domain of heart failure was kept as a held-out test set on which final f1-scores were calculated. The aim was to provide a large, transparent, qualitatively annotated, and diverse dataset to the ATE research community, with the goal of promoting comparative research and thus identifying strengths and weaknesses of various state-of-the-art methodologies. The results show a lot of variation between different systems and illustrate how some methodologies reach higher precision or recall, how different systems extract different types of terms, how some are exceptionally good at finding rare terms, or are less impacted by term length. The current contribution offers an overview of the shared task with a comparative evaluation, which complements the individual papers by all participants.