NLP Question Bank
1. What is natural language processing? Discuss the various steps involved in NLP.
2. What are the challenges and ambiguities in NLP design?
3. Explain different levels of NLP
4. Describe Generic NLP system with a diagram
5. For each sentence, identify whether the different meanings arise from structural
ambiguity, semantic ambiguity or pragmatic ambiguity?
a) Time flies like an arrow
b) He crushed the key to my heart
6. Explain perplexity of any language mode
7. What is Natural Language Processing? Discuss with some applications.
8. Write short noes on Bayes theorem
9. Define random variables with example
10. Explain derivational and inflectional morphology
11. What is the role of FSA in morphological analysis
12. Identify the morphological type (Noun phrase, Verb Phrase, Adjective Phrase)
of following sentence segments
a) important to Bill
b) looked up the tree
13. Write a note on N gram language model.
14. Differentiate between bigram and trigram
15. What is stemming? Explain Porter stemming algorithm in detail?
16. Write short notes on Penn Tree Bank
17. What is Markov process? How HMM is related with Markov Process?
18. What do you mean by transmission probability matrix and emission probability
matrix. Explain with one example
19. What are the limitations of Hidden Markov Model?
20. Explain POS tagging with example
21. Distinguish between semantics, pragmatics and discourse
22. Describe open class words and closed class words with examples
23. Differentiate between different morphemes, with examples.
24. State the difference between hypernymy and hyponymy and give an example of each
25. State the difference between homonymy and polysemy and give an example of each
26. Explain lexicon, lexeme and the different types of relations that hold between
Lexemes
27. Discuss various relations among the word senses.
28. What is meant by Lexicon? How is it useful in NLP?
29. What is meant by the semantics of a natural language, and how this differs from the
pragmatics?
30. Explain the difference of discourse structure from other reference mechanisms
31. Discuss reference resolution problem in detail
32. What are Syntactic and Semantic Constraints on co reference?
33. What do you mean by word sense disambiguation (WSD)? Discuss dictionary based
approach for WSD.
34. Write short notes on
a. Sentiment Analysis
b. Word net
35. Explain direct machine translation
36. Explain text summarization
37. Explain NER
38. Explain Question answer system
39. Explain text categorization in NLP
40. Explain the architecture of an Information Retrieval system with a neat diagram.
41. How do you find the Cosine distance between the documents?
42. How HMM is used for POS tagging? Explain in detail.
44. Consider the following corpus
<s> I tell you to sleep and rest </s>
<s> I would like to sleep for an hour </s>
<s> Sleep helps one to relax </s>
List all possible bigrams. Compute conditional probabilities and predict
the next word for the word “to”.
45. Using the given training corpus, Identify the tags for the sentence " Can Justin watch
Martin" using HMM
Using the given training corpus, Identify the tags for the sentence " The park is a book"
using HMM
46. Calculate the transmission and emission probabilities for the set of sentences below
• Mary Jane can see Will
• Spot will see Mary
• Will Jane spot Mary?
• Mary will pat Spot
Tag the sentence “Will can spot Mary’” using Viterbi algorithm.
47. f(x,y)=ke-(x+y) 0 ≤ x,y ≤ ∞. Find k and marginal densities of x and y.
48. Define mean and variance of a random variable
