• Attempt any five questions.
• All questions carry equal marks.
Define formal grammar and discuss its role in language modeling.
Explain the need for Transducers in morphological parsing.
Write the regular expression pattern for the following user.name@sub.co.in and 1111 1111 1111 1111.
What are some common types of smoothing techniques used in NLP, and how do they differ from each other?
Differentiate key components of Hidden Markov and Maximum Entropy models.
Write short notes on PoS tagging types and issues in word analysis.
Explain how dependency grammar differs from phrase-structure grammar.
Describe disambiguation techniques and challenges in parsing.
Check the acceptance of string s="ababab" using the CYK Algorithm. For the given grammar S AB/BC A BA/a B CC/b C AB/a
Illustrate Word similarity using a thesaurus and distributional methods.
Briefly explain different Bootstrapping methods in NLP.
Explain supervised Word Sense Disambiguation methods with suitable examples.
How can natural language processing create intelligent tutoring systems? Discuss with applications.
Describe the functioning of machine translation and provide examples of its real-world applications.
Explain any two of the following: a) Tokenization b) Unification of feature structures c) Syntax-Driven Semantic analysis d) Man-Machine interfaces
