Rohan-Thoma/Multiple-choice-question-generator-using-NLP

Project aims at generating multiple choice questions along with the options and correct answer using NLP and Large Language Models, so that given any text from any text book , the model will generate multiple choice questions , so that it can aid educators in creating engaging and challenging assessments for their students.

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Emerging

Implements a multi-stage pipeline combining extractive/abstractive summarization, keyword extraction (YAKE, KeyBERT, TopicRank), and T5 transformer-based question generation trained on SQuAD datasets. Generates plausible distractors using WordNet and word sense disambiguation with BERT to create semantically similar wrong answers, avoiding reliance on external APIs for production deployment.

No commits in the last 6 months.

Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 9 / 25
Community 14 / 25

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27

Forks

5

Language

Jupyter Notebook

License

Apache-2.0

Last pushed

Dec 29, 2023

Commits (30d)

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