same word belonging to different lemma

lemmatization.py

living_from_live = "She's living her best life"
living_from_living = "What do you do for a living?"

language = 'en'

#Request to the API
output = client.specific_resource_analysis(
    body={"document": {"text": living_from_live }}, 
    params={'language': language, 'resource': 'disambiguation'
})

#Request to the API
output_2 = client.specific_resource_analysis(
    body={"document": {"text": living_from_living }}, 
    params={'language': language, 'resource': 'disambiguation'
})

#to print TOKEN, POS  and ID (for the concept) in bold at the beginning of the output array:
print (f'\t \033[1mOuput of the first sentence : \033[0m \n') 
print (f'\033[1m{"TOKEN":{20}} {"LEMMA":{15}} {"POS":{6}} \033[0m')

#Syncon stands for "Concept" that we refer to with an ID
for token in output.tokens:
    print (f'{living_from_live [token.start:token.end]:{20}} {token.lemma:{15}} {token.pos:{6}} ')
    
print (f'\t \033[1mOuput of the second sentence : \033[0m \n')   
print (f'\033[1m{"TOKEN":{20}} {"LEMMA":{15}} {"POS":{6}} \033[0m')
for token in output_2.tokens:
    print (f'{living_from_living [token.start:token.end]:{20}} {token.lemma:{15}} {token.pos:{6}} ')