Natural Language Processing Nptel Week 2 Quiz Answers 2026
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Natural Language Processing Nptel Week 2 Quiz Answers (Jan-Apr 2026)
Que.1
When computing the Minimum Edit Distance between two strings of length n and m using Dynamic Programming, what are the time and space complexities required for the standard algorithm?
a) Time: O(n + m), Space: O(n)
b) Time: O(n²), Space: O(1)
c) Time: O(m), Space: O(n)
d) Time: O(nm), Space: O(nm)
Que.2
Consider a Bigram model with a vocabulary size V = 10,000. You encounter a bigram “smart phone” which appeared 0 times in the training data. The word “smart” appeared 500 times. Using Add-One (Laplace) Smoothing, what is the smoothed probability ( P_{\text{Add-1}}(\text{phone} \mid \text{smart}) )?
a) 1 / 500
b) 0 / 500
c) 1 / 10,500
d) 1 / 501
Que.3
In the context of spelling correction, how are Non-word errors distinguished from Real-word errors?
a) Non-word errors are grammatical mistakes; Real-word errors are typos
b) Non-word errors result in a string not found in the dictionary; Real-word errors result in a valid dictionary word
c) Non-word errors only occur in names; Real-word errors occur in verbs
d) Non-word errors are handled by N-grams; Real-word errors are handled by Edit Distance only
Que.4
For the string “bread”, identify which of the following sets of strings has a Levenshtein distance of exactly 1.
a) bead, break, breed, beard, tread
b) read, broad, dread, bred, spread
c) read, broad, dread, bred, bead
d) brand, braid, bead, break, bred
Que.5
You are building a Trigram Language Model (N = 3). Applying the Markov Assumption, how is the probability of the word ( w_n ) approximated?
a) ( P(w_n \mid w_1, w_2, \ldots, w_{n-1}) \approx P(w_n) )
b) ( P(w_n \mid w_1, w_2, \ldots, w_{n-1}) \approx P(w_n \mid w_{n-1}) )
c) ( P(w_n \mid w_1, w_2, \ldots, w_{n-1}) \approx P(w_n \mid w_{n-2}, w_{n-1}) )
d) ( P(w_n \mid w_1, w_2, \ldots, w_{n-1}) \approx P(w_n \mid w_{n-3}, w_{n-2}, w_{n-1}) )
Que.6
Calculate the Levenshtein edit distance between the strings
S₁ = “brisk” and S₂ = “brick”, assuming a cost of 1 for insertion, deletion, and substitution. What is the minimum cost and the operation?
a) Cost 1: Substitution
b) Cost 2: Deletion, Insertion
c) Cost 1: Transposition
d) Cost 0: They are identical
Que.7
What is the primary motivation for applying Laplace (Add-One) Smoothing to N-gram models?
a) To reduce the perplexity of the training data to zero
b) To handle the “zero probability” problem
c) To increase the weight of high-frequency words
d) To remove stop words from the corpus
Que.8
Consider the following training corpus ( C_1 ) consisting of three sentences (all text lowercased):
S1: “the cat sat on the mat”
S2: “the dog sat on the log”
S3: “the cat jumped on the log”
Using Maximum Likelihood Estimation (MLE), calculate the bigram probability ( P(\text{log} \mid \text{the}) ).
a) 2 / 3
b) 1 / 3
c) 2 / 5
d) 1 / 6
Que.9
Using the same corpus ( C_1 ), calculate the Perplexity of the bigram model on the test sentence:
“the cat sat”.
a) √6
b) 6
c) √3
d) 1 / √6
Que.10
In the Dynamic Programming algorithm for Minimum Edit Distance, consider a specific cell where i > 0 and j > 0. The neighboring cells have values:
D(i−1, j) = 5, D(i, j−1) = 5, and D(i−1, j−1) = 4.
If the characters X[i] and Y[j] are identical (match), and the costs are: insertion = 1, deletion = 1, substitution = 2, match = 0, what is the value of D(i, j)?
a) 4
b) 5
c) 6
d) 3
(Jan-Apr 2025)
Course Link: Click Here
1. According to Zipf’s law which statements) is/are correct?
(i) A small number of words occur with high frequency.
(ii) A large number of words occur with low frequency.
a. Both (i) and (ii) are correct
b. Only (ii) is correct
c. Only (i) is correct
d. Neither (i) nor (ii) is correct
2. Consider the following corpus Ci of 4 sentences. What is the total count of unique bi-grams for which the likelihood will be estimated? Assume we do not perform any pre-processing.
tomorrow is Sachin’s birthday
He loves cream chocolates
he is also fond of sweet cake
we will celebrate his birthday with sweet chocolate cake
today is Sneha’s birthday
she likes ice cream
she is also fond of cream cake
we will celebrate her birthday with ice cream cake
a. 24
b. 28
c. 27
d. 23
3. A 4-gram model is a______________order Markov Model.
a. Two
b. Five
c. Four
d. Three
4. Which of these is/are – valid Markov assumptions?
a. The probability of a word depends only on the current word.
b. The probability of a word depends only on the previous word.
c. The probability of a word depends only on the next word.
d. The probability of a word depends only on the current and the previous word.
5. For the string ‘mash’, identify which of the following set of strings has a Levenshtein distance of
1.
a. smash, mas, lash, mushy, hash
b. bash, stash, lush, flash, dash
c. smash, mas, lash, mush, ash
d. None of the above
6. Assume that we modify the costs incurred for operations in calculating Levenshtein distance,
such that both the insertion and deletion operations incur a cost of 1 each, while substitution
incurs a cost of 2. Now, for the string ‘clash’ which of the following set of strings will have an
edit distance of 1?
a. ash, slash, clash, flush
b. flash, stash, lush, blush,
c. slash, last, bash, ash
d. None of the above
7. Given a corpus C2, the Maximum Likelihood Estimation (MLE) for the bigram “dried berries” is
0.45 and the count of occurrence of the word “dried” is 720. For the same corpus C the likelihood
of “dried berries” after applying add-one smoothing is 0.05. What is the vocabulary size of C2?
a. 4780
b. 3795
c. 4955
d. 5780
8. Calculate P(they play in a big garden) assuming a bi-gram language model.
a. 1/8
b. 1/12
c. 1/24
d. None of the above
9. Considering the same model as in Question 7, calculate the perplexity of they play in a big
garden < |s>.
a. 2.289
b. 1.426
C. 1.574
d. 2.178
10. Assume that you are using a bi-gram language model with add one smoothing. Calculate P(they play in a beautiful garden).
a. 4.472 × 101-6
b. 2.236 × 10^-6
c. 3.135 × 10^-6
d. None of the above
Natural Language Processing Nptel Week 2 Quiz Answers
For answers to others Nptel courses, please refer to this link: NPTEL Assignment