Visualize parsing result

This is just a primitive “setup and use” snippet.

It is very easy to use the Jupyter Notebook with nbextensions for visualazing the tests of spaCy model. The displaCy Jupyter extension is a simple extension for Jupyter Notebook that lets you visualize a JSON-formatted dependency parse using the displaCy visualizer.

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1. Install Jupyter Notebook.

2. Install Jupyter nbextension.

    pip install jupyter_contrib_nbextensions
   

3. Install displaCy Jupyter extension.

    jupyter nbextension install --user https://github.com/explosion/spacy-dev-resources/tree/master/jupyter-displacy
   

4. Enable the extension.

    jupyter nbextension enable displacy
   

5. Process whole sentence and visualize the results.

    doc1 = nlp('Dependency tree parsing results can be visualized easily in a notebook.')
    for token in doc1:
        print(token.text, token.lemma_, token.pos_, token.tag_)
    displacy.render(doc1, style='dep', jupyter=True)
   

See: SpaCy Visualizers

See: Possible visualizer options