B.E. (Computer Science Engineering) Eighth Semester (C.B.S.)
Elective - IV : Natural Language Processing TKN/KS/16/7701
P. Pages : 2 *0713*
Time : Three Hours Max. Marks : 80 _____________________________________________________________________ Notes : 1. 2. 3. 4. 5. 6. 7. 8. 9.
How natural language processing system are evaluated? Explain .
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What type of grammar is suitable for natural language processing? How it helps in processing of natural language.
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Explain the difficulties in processing of natural language.
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Natural language has ambiguous constructs. How such ambiguous constructs in NLP is handled.
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What do you understand by N-gram? What is the role of N-gram in NLP.
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b)
Explain the difference between word classes and part-of-speech tagging.
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What is the role of smoothing algorithm in NLP.
b)
Write out the equation for trigram probability estimation.
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Why CFG is used for processing languages. What is generative grammar? How it differs from CFG.
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What are issues in parsing? Discuss various techniques used for parsing with suitable example.
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Solve Question 1 OR Questions No. 2. Solve Question 3 OR Questions No. 4. Solve Question 5 OR Questions No. 6. Solve Question 7 OR Questions No. 8. Solve Question 9 OR Questions No. 10. Solve Question 11 OR Questions No. 12. Due credit will be given to neatness and adequate dimensions. Assume suitable data whenever necessary. Illustrate your answers whenever necessary with the help of neat sketches.
OR 6.
a)
Draw phase structure Tree representing one parse of the following sentences. Make a list of the phrase structure rules that you are assuming. John and Mary bought a refrigerator with three doors.
TKN/KS/16/7701
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P.T.O
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7.
b)
Write an algorithm for converting an arbitrary content-free grammar into Chomskynormal form. Explain with suitable example.
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a)
Write a short note on retrieval of information.
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b)
What are the characteristics of syntax driven semantic analysis.
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OR Develop a set of grammar rules and semantic attachments to handle predictive adjectives such as the one following. i) Flight 308 from New York is expensive ii) Murphy's restaurant is cheap.
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b)
Explain word sense disambiguation in brief.
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a)
State and explain various techniques of text summarization.
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b)
How context sensitive speech conversion in done explain?
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a)
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Explain the need for entity recognition and relation with suitable example.
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b)
Which factors can be modeled and weighted against each other in a pronoun interpretation algorithm.
a)
Explain the procedure for machine translation.
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b)
Describe how Yarowsky's algorithm for word sense disambiguation would process the texts. Illustrate each stage of the algorithm with an example.
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