Edit the code & try spaCy

spaCy v3.4 · Python 3 · via Binder

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# pip install -U spacy

# python -m spacy download en_core_web_sm

import spacy

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# Load English tokenizer, tagger, parser and NER

nlp = spacy.load("en_core_web_sm")

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# Process whole documents

text = ("When Sebastian Thrun started working on self-driving cars at "

        "Google in 2007, few people outside of the company took him "

        "seriously. “I can tell you very senior CEOs of major American "

        "car companies would shake my hand and turn away because I wasn’t "

        "worth talking to,” said Thrun, in an interview with Recode earlier "

        "this week.")

doc = nlp(text)

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# Analyze syntax

print("Noun phrases:", [chunk.text for chunk in doc.noun_chunks])

print("Verbs:", [token.lemma_ for token in doc if token.pos_ == "VERB"])

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# Find named entities, phrases and concepts

for entity in doc.ents:

    print(entity.text, entity.label_)

RUN