Text Simplification using Word Sense Disambiguation Using Knowledge-Based Approach
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Updated
Aug 14, 2017 - Python
Text Simplification using Word Sense Disambiguation Using Knowledge-Based Approach
Slides for tutorials of Statistical Natural Language Processing (SS 2021), Universität des Saarlandes.
This is the implementation of SIGIR - 2005 paper on Iterative translation disambiguation for cross-language information retrieval
Five mini-projects done for the course of Natural Language Technologies held at the Computer Science departement of the University of Turin.
SLI mappings for OMSTI dataset
Master's Thesis in Natural Language Generation
Word Sense Disambiguation using the Lesk algorithm with Word2Vec embeddings
SLI mappings for the Princeton Annotated Gloss Corpus dataset
Implemented a dictionary-based Word Sense Disambiguation(WSD) system that disambiguates the sense by comparing the definitions of the target word to the definitions of relevant words in the context. (Simple Lesk and Corpus Lesk)
Naive Bayes algorithm-based word sense disambiguation implemented from scratch.
Natural Language Processing (NLP) course final project for Word Sense Disambiguation task.
AnnotatedSentence Processing Library
An out-of-the-box, corpus-agnostic query expansion tool for lexical retrieval systems.
Word Sense Annotation on Toloka for RUSSE 2018 WSI&D Task.
Python Makes Sense - a word sense disambiguation project
University of Washington, Masters of Computational Linguistics - LING 571 - Deep Processing Techniques for NLP
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