spacylemma.py

#make sure to download the english model with "python -m spacy download en"

import en_core_web_sm
nlp = en_core_web_sm.load()

doc = nlp(u"""He determined to drop his litigation with the monastry, and relinguish his claims to the wood-cuting and 
fishery rihgts at once. He was the more ready to do this becuase the rights had become much less valuable, and he had 
indeed the vaguest idea where the wood and river in question were.""")

lemma_word1 = [] 
for token in doc:
    lemma_word1.append(token.lemma_)
lemma_word1