A Web Service Discovery host daemon.

Python Implementations of Word Sense Disambiguation (WSD) Technologies.

A crowd sourced collection of interview questions asked in Bangladeshi Tech companies

Making sense embedding out of word embeddings using graph-based word sense induction

Sentiment Classification using Word Sense Disambiguation

Japanese Natural Langauge Processing Libraries

Language Modelling Makes Sense - WSD (and more) with Contextual Embeddings

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.

Make your Linux/macOS/BSD/illumos machine visible in Network view of Windows Explorer

A pipeline for transliteration, spell correction, POS tagging and word sense disambiguation of Hinglish code mixed data to Hindi Devanagari script.

Web Services for Devices (WSD) tools and utilities for cross platform support

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)

Code to train and test Word Sense Disambiguation models based on different pretrained transformers.

Word sense disambiguation using neural models, replicating https://research.google.com/pubs/pub45729.html?authuser=0

Distribution of word meanings in Wikipedia for English, Italian, French, German and Spanish.

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.

Semeval-2013 and -2015 multilingual WSD datasets for BabelNet 4.0