NLP & NLTK

Consider the following Python code snippet that uses the Natural Language Toolkit $($NLTK$)$ for tokenizing text:

from nltk$.$tokenize import sent$\_$tokenize, word$\_$tokenize

text $=$ "I waited for the train. The train was late. Dr$.$ Jiao and Seung Jun took the bus. I looked for

Seung Jun and Dr$.$ Jiao at the bus station."

result $=[$ word$\_$tokenize$(($t$)$ for t in sent$\_$tokenize$($text$)]-$ Q$1.$ How many sublists are contained within result? $,$ Q$2.$ Which sentences forms the third sublists in the result list?

Which sentences forms the third sublists in the result list?

$["$Dr$.",$ "Jiao", "and", "Seung", "Jun", "took", "the", "bus", $"."]$

$[$I$","$Dr$.$ Jiao", "and", "Seung", "Jun", "took", "the", "bus", $"."]$

$[$I$","$Dr$.$ Jiao", "and", "Seung Jun", $"",$ "took", "the", "bus", $"."]$

$[$I$","$Dr$.$ Jiao", "and", "Seung Jun", $"",$ "took", "the bus", $"."]$

$["$Dr$.$ Jiao", "and", "Seung Jun", "took", "the", "bus", $"."],$ Q$3.$ If we want to access the word "bus" from the result, which index would we use?

If we want to access the word "bus" from the result, which index would we use?

result$[2][4]$

result$[2][5]$

result$[2][6]$

result$[2][7]$

result$[2][8]$