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Word Sense Disambiguation using Word Specific models, All word models and Hierarchical models in Tensorflow
SLI mappings for SemCor dataset
The repository contains the implementation of four baseline models for Word Sense Disambiguation, including Lesk, Naive Bayes, K-Nearest Neighbors, and BiLSTM. Additionally, a BERT-based model has been included for comparison. The models have been trained on the SemCor dataset and evaluated on the Senseval and SemEval datasets
Word Sense Disambiguation using the Lesk algorithm with Word2Vec embeddings