ShiZhengyan/IngredientParsing

Dataset and pytorch codes for the paper titled "Attention-based Ingredient Phrase Parser". ESANN 2022.

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Experimental

This project helps conversational AI systems understand cooking instructions by precisely identifying ingredients and their attributes like name, unit, and quantity from natural language. It takes free-form ingredient phrases as input and outputs structured ingredient details. This is useful for developers building virtual personal assistants or smart kitchen apps.

No commits in the last 6 months.

Use this if you are developing a conversational AI system that needs to accurately parse ingredient lists for cooking tasks.

Not ideal if you need a pre-built, ready-to-deploy API for ingredient parsing without any development work.

conversational-AI natural-language-processing virtual-assistant recipe-analysis food-tech
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 8 / 25
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Language

Python

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Last pushed

Dec 17, 2023

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