SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection
Accepted version
Peer-reviewed
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Change log
Authors
Schlechtweg, Dominik
McGillivray, Barbara https://orcid.org/0000-0003-3426-8200
Hengchen, Simon
Dubossarsky, Haim
Tahmasebi, Nina
Abstract
Lexical Semantic Change detection, i.e., the task of identifying words that change meaning over time, is a very active research area, with applications in NLP, lexicography, and linguistics. Evaluation is currently the most pressing problem in Lexical Semantic Change detection, as no gold standards are available to the community, which hinders progress. We present the results of the first shared task that addresses this gap by providing researchers with an evaluation framework and manually annotated, high-quality datasets for English, German, Latin, and Swedish. 33 teams submitted 186 systems, which were evaluated on two subtasks.
Description
Keywords
cs.CL, cs.CL
Journal Title
Conference Name
COLING- The 28th International Conference on Computational Linguistics
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Publisher
ACL
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All rights reserved
Sponsorship
Alan Turing Institute (EP/N510129/1)