/ingredient-parser

A tool to parse recipe ingredients into structured data

Primary LanguagePythonMIT LicenseMIT

Ingredient Parser

The Ingredient Parser package is a Python package for parsing structured information out of recipe ingredient sentences.

Documentation

Documentation on using the package and training the model can be found at https://ingredient-parser.readthedocs.io/.

Quick Start

Install the package using pip

$ python -m pip install ingredient-parser-nlp

Import the parse_ingredient function and pass it an ingredient sentence.

>>> from ingredient_parser import parse_ingredient
>>> parse_ingredient("3 pounds pork shoulder, cut into 2-inch chunks")
ParsedIngredient(
    name=IngredientText(text='pork shoulder', confidence=0.999193),
    size=None,
    amount=[IngredientAmount(quantity='3',
                             unit=<Unit('pound')>,
                             text='3 pounds',
                             confidence=0.999906,,
                             APPROXIMATE=False,
                             SINGULAR=False)],
    preparation=IngredientText(text='cut into 2 inch chunks', confidence=0.999193),
    comment=None,
    purpose=None,
    sentence='3 pounds pork shoulder, cut into 2-inch chunks'
)

Refer to the documentation here for the optional parameters that can be used with parse_ingredient .

Model

The core of the library is a sequence labelling model that is used to label each token in the sentence with the part of the sentence it belongs to. A data set of 75,000 example sentences is used to train and evaluate the model. See the Model Guide in the documentation for mode details.

The model has the following accuracy on a test data set of 20% of the total data used:

Sentence-level results:
	Accuracy: 95.86%

Word-level results:
	Accuracy 98.41%
	Precision (micro) 98.41%
	Recall (micro) 98.41%
	F1 score (micro) 98.41%

Development

The development dependencies are in the requirements-dev.txt file. Details on the training process can be found in the Model Guide documentation.

Before committing anything, install pre-commit and run

pre-commit install

to install the pre-commit hooks.

There is a simple web app for testing the parser with ingredient sentences and showing the parsed output. To run the web app, run the command

$ flask --app webapp run

Screen shot of web app

This requires the development dependencies to be installed.

The dependencies for building the documentation are in the requirements-doc.txt file.