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NLP 24

This document is an examination paper for a B.E. course in Information Technology Engineering, specifically focused on Natural Language Processing. It contains a total of 8 questions, with candidates required to answer specific pairs of questions, and includes instructions for diagram usage and data assumptions. The questions cover various NLP topics such as discourse processing, lexical resources, semantic text mining, and the role of corpora.

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solankarvv04
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12 views2 pages

NLP 24

This document is an examination paper for a B.E. course in Information Technology Engineering, specifically focused on Natural Language Processing. It contains a total of 8 questions, with candidates required to answer specific pairs of questions, and includes instructions for diagram usage and data assumptions. The questions cover various NLP topics such as discourse processing, lexical resources, semantic text mining, and the role of corpora.

Uploaded by

solankarvv04
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PDF, TXT or read online on Scribd
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Total No. of Questions: 8] SEAT No.

8
23
PB2336 [6263]-184 [Total No. of Pages :2

ic-
tat
B.E. (Information Technology Engineering)

8s
NATURAL LANGUAGE PROCESSING

5:1
(2019Pattern) (Semester-VIII) (Elective-V) (414451 C)

02 91
3:5
Time : 2½ Hours] [Max. Marks : 70

0
41
7/0 13
Instructions to the candidates:
1) Answer Q.1 or Q.2, Q.3 or Q.4, Q5 or Q6, Q7 or Q8.
0
5/2
2) Neat diagrams must be drawn wherever necessary.
.23 GP

3) Figures to the right indicate full marks.


4) Assume Suitable data if necessary.
E
81

8
C

23
ic-
Q1) a) Explain steps used in discourse processing. [9]
16

tat
b) What are the different types of ambiguity? Provide an example of each.
8.2

8s
[9]
.24

5:1
91
49

OR
3:5
30
41

Q2) a) What is the role of lexical resources? Explain WordNet in lexical


01
02

semantics? [9]
5/2
GP

b) What is Word Sense Disambiguation? How it is handled in NLP. [9]


7/0
CE
81

8
23
Q3) a) What is role of annotate knowledge in generation of text reports. [8]
.23

ic-
16

b) What is role of NLP in web search? Give suitable example. [9]


tat
8.2

8s

OR
.24

5:1
91

Q4) a) Explain significance of Text Pre-Processing in NLP. Elaborate any method


49

3:5

for Text Pre Processing. [8]


30
41

b) Write a note on “Learning to Annotate Cases with Knowledge Roles”.


01
02

[9]
5/2
GP

Q5) a) What is semantic text mining? Explain with a neat diagram. [6]
7/0

b) Write note on Combination of Probabilistic Classification and Finite-State


CE
81

Sequence. [6]
.23

c) Write in detail the high level representation approaches in text mining.[6]


16
8.2

OR
.24

P.T.O.
49
8
Q6) a) What is probabilistic model? Give examples of probabilistic models and

23
explain any one in detail. [9]

ic-
b) Explain the document separation as sequence mapping problem. [9]

tat
8s
5:1
Q7) a) What is Corpora? What is the role of Corpora? Explain the 3 types of

02 91
3:5
Corpora. [5]

0
b) Explain design feature of IR with a neat diagram. [7]

41
c)
7/0 13
Explain POS Tagger. [5]
0
5/2
.23 GP

OR
E

Q8) a) What is iSTART? List the reading strategies used by ISTART [7]
81

8
C

23
b) Write short note on. [10]

ic-
i) Word Net
16

tat
ii) Frame Net
8.2

8s

.24

5:1
91
49

3:5
30
41
01
02
5/2
GP
7/0
CE
81

8
23
.23

ic-
16

tat
8.2

8s
.24

5:1
91
49

3:5
30
41
01
02
5/2
GP
7/0
CE
81
.23
16
8.2
.24
49

[6263]-184 2

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