Question 1
(a)
Explain the components of NLP.
3 Marks
(b)
Explain applications of NLP in brief.
4 Marks
(c)
Provide a detailed explanation of the various phases in Natural Language Processing.
7 Marks
Gujarat Technological UniversitySummer 2026 Examination
GTU 3170723 Natural Language Processing (NLP) Summer 2026 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 Hours2:30 PM – 5:00 PM
Paper Structure5 QuestionsWith internal OR choices
Question 2
(a)
What is Natural Language Generation? Explain in brief.
3 Marks
(b)
Explain Parts of Speech Tagging and its importance.
4 Marks
(c)
Explain Bi-gram concepts using an example sentence:
“The purpose of our life is to happy”.
7 Marks
OR OPTION
(c)
Explain Unigram, Bi-gram and Tri-gram concepts using an example sentence: “This is a Big Data AI Book”.
7 Marks
Question 3
(a)
Write a short note on Named Entity Recognition
3 Marks
(b)
Explain Chunking in NLP.
4 Marks
(c)
Explain Word Sense Disambiguation with Lesk algorithm.
7 Marks
OR OPTION
(a)
Draw the Dependency tree for a sentence A big black dog runs after a poor cat
3 Marks
(b)
What is Morphology? Explain the approaches to Morphology.
4 Marks
(c)
Enlist Word Sense Disambiguation approaches. Explain any one of them in detail.
7 Marks
Question 4
(a)
What is Sentiment Mining and How Does it Work?
3 Marks
(b)
Analyze any application of NLP using the concept of Cross-Lingual IR.
4 Marks
(c)
Explain types of IR-based question answering models.
7 Marks
OR OPTION
(a)
Explain Precision and Recall in brief.
3 Marks
(b)
What is Information Extraction? How Does Information Extraction Work?
4 Marks
(c)
Write a detailed note on Relation Extraction via Supervised Learning.
7 Marks
Question 5
(a)
Describe Knowledge Based Machine Translation System.
3 Marks
(b)
Draw and Explain Encoder- Decoder architecture in detail.
4 Marks
(c)
What are the different approaches to machine translation? Explain in details with its pros and cons.
7 Marks
OR OPTION
(a)
Explain the dimensions used to evaluate Machine Translation.
3 Marks
(b)
Explain Deep Neural Machine Translation
4 Marks
(c)
Explain the concept of SMT and NMT in detail. Also state the differences between them with example.
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) (Summer 2026, 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.