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Natural Language Processing (NLP) has been widely used in the semanticanalysis in recent years. Our paper mainly discusses a methodology to analyzethe effect that context has on human perception of similar words, which is thethird task of SemEval 2020. We apply several methods in calculating thedistance between two embedding vector generated by Bidirectional EncoderRepresentation from Transformer (BERT). Our team will_go won the 1st place inFinnish language track of subtask1, the second place in English track ofsubtask1.

An Accurate Model for Predicting the (Graded) Effect of Context in Word Similarity Based on Bert