Question 1
(a)
Briefly explain component of NLP.
3 Marks
(b)
Describe advantages and disadvantages of Natural Language Processing.
4 Marks
(c)
Elaborate various phases in Natural Language Processing.
7 Marks
Gujarat Technological UniversityWinter 2025 Examination
GTU 3170723 Natural Language Processing (NLP) Winter 2025 Paper Solution & PDF
B.E. · Computer Engineering · Semester 7 · Subject Code: 3170723
Total Marks70 MarksExternal theory exam
Passing Marks23 Marks33% minimum cutoff
Exam Duration2.5 Hours10:30 AM – 1:00 PM
Paper Structure5 QuestionsWith internal OR choices
Question 2
(a)
How does Natural Language Generation works?
3 Marks
(b)
Describe Part-of-Speech Tagging with suitable example.
4 Marks
(c)
Enlist various Smoothing Techniques. Explain any one in detail.
7 Marks
OR OPTION
(c)
Explain Unigram, Bi-gram and Tri-gram concepts using an example sentence: “Life is either a daring adventure or nothing at all”.
7 Marks
Question 3
(a)
Describe skip-gram.
3 Marks
(b)
Explain “Continuous bag of words” with an example.
4 Marks
(c)
Describe nearest neighbor algorithm for Word Sense Disambiguation.
7 Marks
OR OPTION
(a)
Explain perplexity with suitable example.
3 Marks
(b)
Describe Embedding representations for words Lexical Semantics with example.
4 Marks
(c)
How does the Lesk algorithm help in Word Sense Disambiguation?
7 Marks
Question 4
(a)
What is sentiment mining? Provide a brief explanation.
3 Marks
(b)
Write a short note on Named Entity Recognition.
4 Marks
(c)
Explain the concept of Cross-Lingual Information Retrieval in detail.
7 Marks
OR OPTION
(a)
How is Text Classification and Text Summarization works in NLP?
3 Marks
(b)
State different algorithms used for relation extraction.
4 Marks
(c)
Explain stages of IR-based question answering models.
7 Marks
Question 5
(a)
Discuss the Problems of Machine Translation.
3 Marks
(b)
Explain neural machine translation with suitable example.
4 Marks
(c)
How is parameter learning conducted in Statistical Machine Translation (SMT)? Illustrate with an appropriate example.
7 Marks
OR OPTION
(a)
Explain translation divergence in brief.
3 Marks
(b)
Describe Rule Based Machine Translation System.
4 Marks
(c)
Explain Encoder-decoder Model of Machine Translation with architecture.
7 Marks
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About this Examination Paper & Attribution
Official Gujarat Technological University (GTU) examination paper and step-by-step solutions for Natural Language Processing (NLP) (Winter 2025, B.E. · Computer Engineering, Sem 7). Features complete 70-mark regular & remedial examination pattern, official marking distribution across all 5 questions, and direct 1-click official PDF download.
Transcribed for student exam preparation from Gujarat Technological University official examination archives. Questions, syllabus guidelines, and curriculum marking schemes remain the intellectual property of Gujarat Technological University.