In this paper, we present our contribution in SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection, where we systematically combine existing models for unsupervised capturing of lexical semantic change across time in text corpora of German, English, Latin and Swedish. In particular, we analyze the score distribution of existing models. Then we define a general classification threshold, adjust it independently to each of the models and measure the models' score certainty. Finally, using both the threshold and score certainty, we aggregate the models for the two sub-tasks: binary classification and ranking.
CITATION STYLE
Amar, E., & Liebeskind, C. (2020). JCT at SemEval-2020 Task 1: Combined Semantic Vector Spaces Models for Unsupervised Lexical Semantic Change Detection. In 14th International Workshops on Semantic Evaluation, SemEval 2020 - co-located 28th International Conference on Computational Linguistics, COLING 2020, Proceedings (pp. 90–97). International Committee for Computational Linguistics. https://doi.org/10.18653/v1/2020.semeval-1.9
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