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 ๐ 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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