wsd

A Web Service Discovery host daemon.

Python Implementations of Word Sense Disambiguation (WSD) Technologies.

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

A package for working with whole-slide data including a fast batch iterator that can be used to train deep learning models.

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

A Word Sense Disambiguation system integrating implicit and explicit external knowledge.

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"

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

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.

Exploiting the global WordNet graph to perform WSD

WSD for Word-in-Context (WiC) disambiguation, experimenting with BERT feature-based and fine-tuning approaches (GlossBERT)

Official repository of the paper "Analyzing Homonymy Disambiguation Capabilities of Pretrained Language Models".

Repo for the paper "MWE as WSD: Solving Multi-Word Expression Identification with Word Sense Disambiguation"

Working with WSD scanner from Linux

Universal network scanner to Paperless-NGX bridge

[🏆 Azure Prize at TreeHacks] readAR -- 🌲 TreeHacks 2020 Backend

Word sense disambiguation project that uses a wikipedia dump and discovers relationship with a graph. Cooked with python microservices, neo4j, elasticsearch