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{Week 1} Natural Language Processing NPTEL Assignment Answers 2025

By / January 29, 2025

NPTEL Natural Language Processing Week 1 Assignment Answers 2025

1. In a corpus, you found that the word with rank 4th has a frequency of 250. What can be the best guess for the rank of a word with frequency 125?

  • 1. 2
  • 2. 4
  • 3. 6
  • 4. 8
Answer :- b

2. In the sentence, “In Delhi I took my hat off. But I can’t put it back on.”, total number of
word tokens and word types are:

  • 1. 14, 13
  • 2. 13, 14
  • 3. 15, 14
  • 4. 14, 15
Answer :- a

3. Let the rank of two words, w1 and w2, in a corpus be 1600 and 100, respectively. Let m1 and m2 represent the number of meanings of w1 and w2 respectively. The ratio m1 : m2 would tentatively be

  • 1. 1:4
  • 2. 4:1
  • 3. 1:2
  • 4. 2:1
Answer :- For Answers Click Here

4. What is the valid range of type-token ratio of any text corpus?

  1. TTRE(0,1] (excluding zero)
  2. TTRe[0,1]
  3. TTRE[-1,1]
  4. TTRE[0, +∞] (any non-negative number)
Answer :-

5. If first corpus has TTR1 = 0.06 and second corpus has TTR2 = 0.105, where TTR1 and TTR2 epresents type/token ratio in first and second corpus respectively, then

  • 1. First corpus has more tendency to use different words.
  • 2. Second corpus has more tendency to use different words.
  • 3. Both a and b
  • 4. None of these
Answer :-

6. Which of the following is/are true for the English Language?

  • 1. Lemmatization works only on inflectional morphemes and Stemming works only on derivational morphemes.
  • 2. The outputs of lemmatization and stemming for the same word might differ.
  • 3. Output of lemmatization are always real words
  • 4. Output of stemming are always real words
Answer :- For Answers Click Here

7. An advantage of Porter stemmer over a full morphological parser?

  • 1. The stemmer is better justified from a theoretical point of view
  • 2. The output of a stemmer is always a valid word
  • 3. The stemmer does not require a detailed lexicon to implement
  • 4. None of the above
Answer :-

8. Which of the following are not instances of stemming? (as per Porter Stemmer)

  • 1. are →> be
  • 2. plays -> play
  • 3. saw -> s
  • 4. university -> univers
Answer :-

9. What is natural language processing good for?

  • 1. Summarize blocks of text
  • 2. Automatically generate keywords
  • 3. Identifying the type of entity extracted
  • 4. All of the above
Answer :-

10. What is the size of unique words in a document where total number of words = 12000. K = 3.71 Beta = 0.69?

  • 1. 2421
  • 2. 3367
  • 3. 5123
  • 4. 1529
Answer :- For Answers Click Here

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