# import Brown corpus from NLTK
import nltk
from nltk.corpus import brown

# ask the user for the sequence of parts of speech
pattern = raw_input("enter your pattern(pos1+pos2+pos3): ")

# split the pattern into three tags: p1, p2 and p3
elt_pattern = pattern.split("+")

# choose the first document of brown corpus
# find all the tagged words and put them into a list named corpus
doc = brown.fileids()
corpus = brown.tagged_words(doc[0])

# allocate the three tags to p1, p2 and p3
p1 = elt_pattern[0]
p2 = elt_pattern[1]
p3 = elt_pattern[2]

# create a for loop to match words' tags with the three tags
size = len(corpus)-2
for i in range(size):
  if corpus[i][1]==p1 and corpus[i+1][1]==p2 and corpus[i+2][1]==p3:
  print str(corpus[i]) + " " + str(corpus[i+1])+ " " + str(corpus[i+2]) + "\n"