A state-of-the-art library for parsing multinational street addresses using deep learning

Here is deepparse.

Deepparse is a state-of-the-art library for parsing multinational street addresses using deep learning.

Use deepparse to

  • Use the pre-trained models to parse multinational addresses,
  • retrain our pre-trained models on new data to parse multinational addresses,
  • retrain our pre-trained models with your own prediction tags easily.

Read the documentation at deepparse.org.

Deepparse is compatible with the latest version of PyTorch and Python >= 3.7.

Countries and Results

We evaluate our models on two forms of address data

  • clean data which refers to addresses containing elements from four categories, namely a street name, a
    municipality, a province and a postal code,
  • incomplete data which is made up of addresses missing at least one category amongst the aforementioned ones.

You can get our dataset here.

Clean

 

 

 

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