AKTU MCA Natural Language Processing (BMC053) Question Paper 2025-26

Note: Attempt all Sections. If require any missing data; then choose suitably.

Section A

Q1. Attempt all questions in brief · 2 × 7 = 14 marks

1. Define Natural Language Processing. Mention any two goals of NLP.
2. List any four levels of language analysis used in Natural Language Understanding.
3. State any two real - world applications of NLP and mention their purpose.
4. What is parsing in NLP? Name any two types of parsers.
5. Define context - free grammar. Give one example of a grammar rule.
6. What is Part - of - Speech tagging? Why is it required in NLP?
7. Define lexical ambiguity with a suitable example.

Section B

Q2. Attempt any three of the following · 7 × 3 = 21 marks

1. Explain different levels of language analysis in NLP. Discuss how these levels help in building Natural Language Understanding systems.
2. Analyze the role of NLP in machine translation and database interface applications with suitable examples.
3. Explain top - down and bottom - up parsing techniques. Compare their working with a suitable sentence example.
4. Discuss feature systems in English grammar. Explain how morphological analysis and lexicon support parsing with features.
5. Explain probabilistic language processing. Discuss how lexical probabilities are obtained and used in Part - of - Speech tagging.

Section C

Q3

Attempt any one part of the following · 7 × 1 = 7 marks

1. Describe the organization of a Natural Language Understanding system. Explain the role of representation and understanding in NLP.
2. Explain the outline of English syntax. Discuss the importance of noun phrases, verb phrases and sentence structure in NLP.

Q4

Attempt any one part of the following · 7 × 1 = 7 marks

1. Explain semantics and knowledge representation in NLP. Discuss their importance in language understanding systems.
2. Analyze the use of NLP in database interface systems. Explain how natural language queries are converted into structured database queries.

Q5

Attempt any one part of the following · 7 × 1 = 7 marks

1. Explain grammar and sentence structure in NLP. Describe top - down chart parsing with a suitable example.
2. Describe Transition Network Grammars and Augmented Transition Networks. Explain their use in parsing natural language sentences.

Q6

Attempt any one part of the following · 7 × 1 = 7 marks

1. Explain auxiliary verbs and verb phrases in natural language grammar. Discuss their role in sentence interpretation.
2. Describe the movement phenomenon in language. Explain how questions can be handled using context - free grammars.

Q7

Attempt any one part of the following · 7 × 1 = 7 marks

1. Explain Probabilistic Context - Free Grammar. Discuss how it helps in handling and evaluating syntactic ambiguity.
2. Explain word senses and ambiguity. Describe how ambiguity can be encoded in logical form with a suitable example.

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