GTU · BE Computer · Semester 7
GTU 3170723 Natural Language Processing (NLP) Old Question Papers PDF
Official Gujarat Technological University (GTU) old question papers PDF (Regular & Remedial) and step-by-step solved questions for Natural Language Processing (NLP) across 2025 – 2026 examinations.
21 questions GTU asked more than onceAsked in all 3 papers: Provide a detailed explanation of the various phases in Natural Language Processing.See listExam papers
Most repeated questions
21 questions GTU set in two or more of 3 papers, most repeated first. Tap a year to open that paper at the question.
Provide a detailed explanation of the various phases in Natural Language Processing.
Explain Bi-gram concepts using an example sentence: “The purpose of our life is to happy”.
Summer 2026 Q2c Summer 2026 Q2c OR Winter 2025 Q2c OR Summer 2025 Q3b
Write a detailed note on Relation Extraction via Supervised Learning.
Explain Parts of Speech Tagging and its importance.
Analyze any application of NLP using the concept of Cross-Lingual IR.
Explain Deep Neural Machine Translation
Explain the components of NLP.
Write a short note on Named Entity Recognition
What is Sentiment Mining and How Does it Work?
Explain Word Sense Disambiguation with Lesk algorithm.
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Enlist Word Sense Disambiguation approaches. Explain any one of them in detail.
Explain types of IR-based question answering models.
How is parameter learning conducted in Statistical Machine Translation (SMT)? Illustrate with an appropriate example.
Enlist various Smoothing Techniques. Explain any one in detail.
Explain applications of NLP in brief.
Draw and Explain Encoder- Decoder architecture in detail.
Describe Embedding representations for words Lexical Semantics with example.
What is Natural Language Generation? Explain in brief.
Describe skip-gram.
How is Text Classification and Text Summarization works in NLP?
Discuss the Problems of Machine Translation.
Which branches take this subject
GTU's syllabus lists 3170723 for 2 branches. One set of papers serves all of them.
Semester 7, elective: 2 branches
Computer Engineering, Computer Science & Engineering
Other Semester 7 subjects
Common questions
Are these GTU 3170723 Natural Language Processing papers valid for both Regular and Remedial exams?
Yes. Gujarat Technological University (GTU) follows the same 70-mark syllabus, exam blueprint, and 23-mark passing cutoff for both Regular and Remedial (ATKT/backlog) examinations. All 3 past exam sessions (2025 – 2026) serve as comprehensive preparation for either attempt.
How can I download GTU 3170723 Natural Language Processing old question papers PDF?
You can download official GTU 3170723 original question paper PDFs directly from the table above with 1 click and zero deceptive ads or wait timers. Every paper also includes interactive online questions with AI study prompts.
What is the passing mark for GTU Natural Language Processing (3170723)?
The external theory exam carries 70 marks. The minimum passing cutoff is 23 marks (33%). Exam duration is 2.5 hours.
What is the GTU exam pattern for 3170723?
The examination contains 5 main questions of 14 marks each, totaling 70 marks. Questions 2 through 5 provide internal OR choices, typically split into 3-mark, 4-mark, and 7-mark questions.