semcor

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Sshanu / Hierarchical-Word-Sense-Disambiguation-using-WordNet-Senses

Word Sense Disambiguation using Word Specific models, All word models and Hierarchical models in Tensorflow

deep-neural-networks deep-learning tensorflow crf lstm wordnet word-sense-disambiguation attention convolutional-neural-networks hierarchical part-of-speech all attention-mechanism hierarchical-models single one-million-dataset semcor single-word-sense-disambiguation all-word-sense-disambiguation

Updated Jun 12, 2020
Jupyter Notebook

GliteTech / research-semcor-relabeling

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Full-corpus SemCor relabeling with GPT-5.5 and Gemma, controlled BEM/ESCHER/ConSeC retraining, and the Glite LENS bi-encoder - reproducibility record for the lexEn/SenseBench WSD paper

nlp reproducible-research dataset wordnet wsd word-sense-disambiguation semcor bi-encoder llm

Updated Jul 18, 2026
Python

Abhi7410 / Word-Sense-Disambiguation

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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 semeval bilstm semcor bert-fine-tuning