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from spacy.lang.en import English
# Load English tokenizer, tagger, parser, NER and word vectors
nlp = English()
# Create the pipeline 'sentencizer' component
sbd = nlp.create_pipe('sentencizer')
# Add the component to the pipeline
text = """Founded in 2002, SpaceX’s mission is to enable humans to become a spacefaring civilization and a multi-planet
species by building a self-sustaining city on Mars. In 2008, SpaceX’s Falcon 1 became the first privately developed
liquid-fuel launch vehicle to orbit the Earth."""
# "nlp" Object is used to create documents with linguistic annotations.
doc = nlp(text)
# create list of sentence tokens
sents_list = []
for sent in doc.sents:
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