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.
Master's Thesis in Natural Language Generation
Word Sense Disambiguation using the Lesk algorithm with Word2Vec embeddings
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
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.
Word Sense Annotation on Toloka for RUSSE 2018 WSI&D Task.
Evaluation (and some implementations/adaptations) of WSD systems for Finnish
Word2Vec Tensorflow implementation with word sense disambiguation.
Natural Language Processing (NLP) course final project for Word Sense Disambiguation task.
AnnotatedSentence Processing Library
An off-the-shelf, corpus-agnostic query expansion tool for lexical retrieval systems.
Implementing Multilingual WSD using [Normal, Atten]BiLSTM, Seq2Seq[Atten], Multitask WSD
Evaluating context-sensitive word meaning understanding in pair of sentences for BERT and GloVe+BiLSTM using WiC dataset | A3 for COL772 course (Fall 21)
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