1 - "Mr. Green killed Colonel Mustard in the study with the candlestick. Mr. Green is not a very nice fellow."
2 - "Professor Plumb has a green plant in his study."
3 - "Miss Scarlett watered Professor Plumb's green plant while he was away from his office last week."

l1 = 19
l2 = 9
l3 = 16

q1 - "green"
q1 = [0.0, 0.71]

1 = [0.0, 0.0747]
2 = [0.0, 0.1555]
3 = [0.0, 0.0875]

green : total count = 4, idf = 0.71
mr : total count = 2, idf = 1.40
the : total count = 2, idf = 1.40
plant : total count = 2, idf = 1.40

q2 = "Mr. Green"
q2 = [1.4, 0.71]

1 = [0.147, 0.0747]
2 = [0, 0.1555]
3 = [0, 0.0875]

q3 = "the green plant"
q3 = [0.5, 0.25, 0.5]

1 = [1, 0.5, 0]
2 = [0, 0.25, 0.5]
3 = [0, 0.25, 0.5]

Inverse Index as a trie
values are {docId: score} where score is the sum of tf across fields, with multipliers applied
when querying calculate the idf and multiply it by the tf

for a multi term query generate a vector using the idf
find all the documents that match both queries, and generate a tf*idf 

word: {
  totalCount: 123,
  docs: 
}