BRUMS at SemEval-2020 Task 3: Contextualised Embeddings for Predicting the (Graded) Effect of Context in Word Similarity

October 13, 2020 ยท Declared Dead ยท ๐Ÿ› International Workshop on Semantic Evaluation

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Authors Hansi Hettiarachchi, Tharindu Ranasinghe arXiv ID 2010.06269 Category cs.CL: Computation & Language Cross-listed cs.AI Citations 14 Venue International Workshop on Semantic Evaluation Last Checked 4 months ago
Abstract
This paper presents the team BRUMS submission to SemEval-2020 Task 3: Graded Word Similarity in Context. The system utilises state-of-the-art contextualised word embeddings, which have some task-specific adaptations, including stacked embeddings and average embeddings. Overall, the approach achieves good evaluation scores across all the languages, while maintaining simplicity. Following the final rankings, our approach is ranked within the top 5 solutions of each language while preserving the 1st position of Finnish subtask 2.
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