Extract relevant vocabulary from a document
Not sure if this is what you are looking for. Couldn't understand your question properly do you want 4-grams then this is the way you could do it. Assuming you have cleaned your text file by eliminating articles.

from nltk import ngrams
file=open('abc.txt','r')
txt = file.read()
n = 4
fourgrams = ngrams(txt.split(), n)
for grams in fourgrams:
  print (grams)


In case your file abc.txt contains "This is random text to demonstrate the use of n-grams"

OUTPUT:
('This', 'is', 'random', 'text')
('is', 'random', 'text', 'to')
('random', 'text', 'to', 'demonstrate')
('text', 'to', 'demonstrate', 'the')
('to', 'demonstrate', 'the', 'use')
('demonstrate', 'the', 'use', 'of')
('the', 'use', 'of', 'n-grams')


If you do not want repetition then 

words = 'This is random text we’re going to split apart'
x=[]
for word in words.split():
    x.append(word)
    if len(x) == 4:
        print(x)
        x=[]
print(x)

OUTPUT:
['This', 'is', 'random', 'text']
['we’re', 'going', 'to', 'split']
['apart']