JRC1995/Dynamic-Memory-Network-Plus

Implementation of Dynamic Memory Network Plus for Question-Answering. Tested on Induction tasks of bAbi 10K dataset.

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Experimental

This project helps train a question-answering system that can understand a story and answer questions about it. You provide a collection of facts or statements (the 'story') and a question related to those facts, and the system attempts to provide the correct answer. It's designed for researchers or developers working on natural language understanding and machine comprehension tasks.

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Use this if you are a researcher or NLP engineer looking to experiment with or benchmark a Dynamic Memory Network Plus implementation for question-answering on datasets like bAbi tasks.

Not ideal if you need a production-ready, highly accurate question-answering system for complex, real-world data, as this implementation is for research and experimentation.

natural-language-processing question-answering machine-comprehension artificial-intelligence-research
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 0 / 25

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Language

Jupyter Notebook

License

MIT

Last pushed

Dec 01, 2017

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