CS476_NLP_QUiz

What is tokenization in text processing?

• • Converting speech into text

• Splitting text into meaningful chunks like words or phrases

• Translating one language into another

• Summarizing a document

Which of the following is NOT a common text preprocessing step?

• Lowercasing

• Stemming

• Language translation

• Removing stopwords

Which of the following is an example of a POS tag?

• NN (Noun)

• VB (Verb)

• JJ (Adjective)

• All of the above

What is a unigram language model?

• A model that predicts the next word based on the previous word

• A model that predicts a word based on its own frequency

• A model that predicts sentences based on word pairs

• A model that captures grammatical structure in sentences

Which algorithm is commonly used for spelling correction?

• Viterbi Algorithm

• Damerau-Levenshtein Distance

• SVM

• K-means Clustering

Why is smoothing important in language modeling?

• To reduce the vocabulary size

• To assign probability to unseen events

• To eliminate grammatical errors

• To increase model efficiency

Which of the following is used for sequential tagging tasks like POS tagging and Named Entity Recognition?

• MaxEnt

• Conditional Random Fields (CRF)

• Both a and b

• None of the above

In which of the following tasks is sequential tagging important?

• Text summarization

• Tokenization

• Named Entity Recognition (NER)

• Word embedding generation

Constituency parsing divides a sentence into:

• Words

• Constituents like noun phrases and verb phrases

• Topics

• Sentences

Which of the following algorithms is used for syntactic parsing?

• CYK Algorithm

• Naive Bayes

• K-Nearest Neighbors

• Expectation-Maximization