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arXiv · 2005.06602

CIRCE at SemEval-2020 Task 1: Ensembling Context-Free and Context-Dependent Word Representations

Martin Pömsl·Roman Lyapin
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Abstract

This paper describes the winning contribution to SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection (Subtask 2) handed in by team UG Student Intern. We present an ensemble model that makes predictions based on context-free and context-dependent word representations. The key findings are that (1) context-free word representations are a powerful and robust baseline, (2) a sentence classification objective can be used to obtain useful context-dependent word representations, and (3) combining those representations increases performance on some datasets while decreasing performance on others.

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Martin Pömsl, Roman Lyapin. 2020-04-30. CIRCE at SemEval-2020 Task 1: Ensembling Context-Free and Context-Dependent Word Representations. https://arxiv.org/abs/2005.06602

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