Natural Language Processing Nptel Week 1 Quiz Answers
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Natural Language Processing Nptel Week 1 Quiz Answers (Jan-Apr 2025)
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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
4. What is the valid range of type-token ratio of any text corpus?
- TTRE(0,1] (excluding zero)
- TTRe[0,1]
- TTRE[-1,1]
- TTRE[0, +∞] (any non-negative number)
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
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
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
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
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
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
Natural Language Processing Nptel Week 1 Quiz Answers
For answers to others Nptel courses, please refer to this link: NPTEL Assignment