Gayatri Venugopal


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RS_GV at SemEval-2021 Task 1: Sense Relative Lexical Complexity Prediction
Regina Stodden | Gayatri Venugopal
Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)

We present the technical report of the system called RS_GV at SemEval-2021 Task 1 on lexical complexity prediction of English words. RS_GV is a neural network using hand-crafted linguistic features in combination with character and word embeddings to predict target words’ complexity. For the generation of the hand-crafted features, we set the target words in relation to their senses. RS_GV predicts the complexity well of biomedical terms but it has problems with the complexity prediction of very complex and very simple target words.