There are 2 repositories under wsd topic.
Making sense embedding out of word embeddings using graph-based word sense induction
Sentiment Classification using Word Sense Disambiguation
Japanese Natural Langauge Processing Libraries
A package for working with whole-slide data including a fast batch iterator that can be used to train deep learning models.
A Word Sense Disambiguation system integrating implicit and explicit external knowledge.
Web Services for Devices (WSD) tools and utilities for cross platform support
A pipeline for transliteration, spell correction, POS tagging and word sense disambiguation of Hinglish code mixed data to Hindi Devanagari script.
Make your Linux/macOS/BSD/illumos machine visible in Network view of Windows Explorer
Code and CoarseWSD-20 datasets for "Language Models and Word Sense Disambiguation: An Overview and Analysis"
A system for unsupervised knowledge-free interpretable word sense disambiguation based on distributional semantics
repository for practice *nix terminal (Ubuntu prefer)
Word sense disambiguation using neural models, replicating https://research.google.com/pubs/pub45729.html?authuser=0
Code to train and test Word Sense Disambiguation models based on different pretrained transformers.
Distribution of word meanings in Wikipedia for English, Italian, French, German and Spanish.
WSD for Word-in-Context (WiC) disambiguation, experimenting with BERT feature-based and fine-tuning approaches (GlossBERT)
Exploiting the global WordNet graph to perform WSD
[🏆 Azure Prize at TreeHacks] readAR -- 🌲 TreeHacks 2020 Backend
Semeval-2013 and -2015 multilingual WSD datasets for BabelNet 4.0
This project is a text summarization system that leverages word sense disambiguation and pre-trained T5 models. It identifies and summarizes repeating words with different meanings, using spaCy for NLP and an n-gram model for candidate word selection. It compares summaries using Rouge scores and outputs the best one. Written in Python with Flask.
NLP: Word Sense Disambiguation (WSD) 📚 on python 3 🐍.
A fast Python 3 Word-Sense Disambiguation package (WSD) using the extended LESK algorithm
Word sense disambiguation project that uses a wikipedia dump and discovers relationship with a graph. Cooked with python microservices, neo4j, elasticsearch
Code and data for the paper 'Unsupervised Word Polysemy Quantification with Multiresolution Grids of Contextual Embeddings'
Repo for the paper "MWE as WSD: Solving Multi-Word Expression Identification with Word Sense Disambiguation"
Readers for NLP Datasets
Data for discrimination of word senses using hypernyms
Simple profanity filter in python
Neural WSD with Transformers and candidate masking
Supervised end-to-end neural architecture that learns how to disambiguate words inside a text.