# NPTEL Natural Language Processing Week 3 Assignment Answers 2024

## NPTEL Natural Language Processing Week 3 Assignment Answers 2024

1. Let’s assume the probability of rolling three (3), two times in a row of a
uniform dice is p. Consider a sentence consisting of N random digits. A model assigns
probability to each of the digit with the probability p. Find the perplexity of the sentence.

1. 10
2. 6
3. 36
4. 3

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2. Which of the following is false?

1.Derivational morphology creates new words by changing part-of-speech
2. Inflectional morphology creates new forms of the same word
3. Reduplication is not a morphological process
4. Suppletion is a morphological process

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3. Assume that “x” represents the input and “y” represents the tag/label. Which
of the following mappings are correct?

1. Generative Models – learn Joint Probability p(x, y) |
2. Discriminative Models – learn Joint Probability p(x, y)
3. Generative Models – learn Posterior Probability p(y | x) directly
4. Discriminative Models – learn Posterior Probability p(y | x) directly
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4. Which one of the following is an example of the discriminative model?

1. Naive Bayes
2. Bayesian Networks
3. Hidden Markov models
4. Logistic Regression
`Answer :- `

5. Natural language processing is essentially the study of the meaning of the
words a human says or writes. Natural language processing is all around us all the time, but it also happens to be a way to improve the chatbot or product we interact with on a regular basis. Natural language processing is all about mimicking our own language patterns. Natural language processing can also improve the efficiency of business transactions and customer care. Natural language processing is the application of computer technology.

Suppose we want to check the probabilities of the final words that succeed the string language processing in the above paragraph. Assume d= 0; it is also given that no of unigrams = 78, no of bigrams = 122, no of trigrams = 130,, Question 6 and Question 7 are related to Question 5 corpus.
Solve the question with the help of Kneser-Ney backoff technique.

What is the continuation probability of “is” ?

1. 0.0078
2. 0.0076
3. 0.0307
4. 0.0081
`Answer :- `

6. What will be the value of P(is| language processing) using Kneser-Ney

1. 0.5
2. 0.6
3. 0.8
4. 0.7
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7. What is the value of P(can| language processing)? Please follow the
paragraph in Question 5

1. 0.1
2. 0.02
3. 0.3
4. 0.2
`Answer :- `

8. Which of the following morphological process is true for motor+hotel –
motel?

1. Suppletion
2. Compounding
3. Blending
4. Clipping
`Answer :- `

9.

`Answer :- `

10. Which of the following is/are true?

1. Only a few non-deterministic automation can be transformed into a deterministic one
2. Recognizing problem can be solved in quadratic time in worst case
3. Deterministic FSA might contain empty (e) transition
4. There exist an algorithm to transform each automation into a unique equivalent
automation with the least no of states
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