Spacy memo

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| Words count in article 128 
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nlp = spacy.load('en_core_web_sm') 

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nlp = spacy.load('en_core_web_sm', disable=['tagger', 'parser', 'ner'])

To use lemma of spacy, consider include the pipe tagger because this will influence the effect of lemmatization:

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nlp = spacy.load('en_core_web_sm') 
doc = nlp("This is my second time.")
for token in doc:
    print(token, token.lemma_) 

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This this
is be
my -PRON-
second second
time time
. .

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nlp = spacy.load('en_core_web_sm', disable=['parser', 'ner']) 
doc = nlp("This is my second time.")
for token in doc:
    print(token, token.lemma_) 

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This this
is be
my -PRON-
second second
time time
. .

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nlp = spacy.load('en_core_web_sm', disable=['tagger', 'parser', 'ner']) 
doc = nlp("This is my second time.")
for token in doc:
    print(token, token.lemma_) 

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This This
is be
my my
second 2
time time
. .