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CRF works quite well, it's actually what I utilize right now to approach recipe parsing on https://cookalo.com/. It's based on CRFsuite with Python bindings for data training on already labeled recipes. If you build your own app and want to do some comparison, feel free to run some benchmarks against it.

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Very cool! It sounds like you followed a similar approach that the NY Times used in their recipe parsing approach, correct?

How does your API handle ingredients with multiple options (e.g. "1 1/2 cups seedless red or green grapes")?

Yes, that's correct, it's similar to the mechanisms NY Times guys were using and I've been focusing on the datasets to feed the CRF with as it's what drives the whole thing. This is the output I've got based on your example: [ { "unit": "cup", "input": "1$1/2 cups seedless red or green grapes", "name": "red grapes", "qty": "1$1/2", "comment": "seedless or green" } ]

Don't hesitate to try the API out by pasting some examples to the white box on the site and pressing the "Try it out!" button, it's interactive :)

Don't hesitate to try the API out by pasting some examples to the white box on the site and pressing the "Try it out!" button, it's interactive

Sweet, I didn't realize it was interactive. I'll give it a try!

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