Which of the following tasks is not typically considered a part of NLP?

• Machine Translation

• Sentiment Analysis

• Image Recognition

• Speech Recognition

What does stemming refer to in NLP?

• The process of splitting text into sentences

• The removal of stop words from a text

• The reduction of words to their base or root form

• The conversion of speech to text

In the context of NLP, what does NER stand for?

• Natural Entity Resolution

• Named Entity Recognition

• Normalized Error Rate

• Neural Entity Regression

What is an n-gram in the context of NLP?

• A single word

• A sequence of 'n' words

• A phrase with at least one stop word

• A type of neural network for processing text

Given the scenario, "Sneha and Naira are discussing the sentence 'Natural Language Processing is fascinating,' what is the bigram representation?

• ["Natural", "Language", "Processing", "is", "fascinating"]

• ["Natural Language", "Language Processing", "Processing is", "is fascinating"]

• ["Natural", "Language", "is", "fascinating"]

• ["Natural Language Processing", "is fascinating"]

6. Why is text normalization important in the field of customer reviews analysis?

• To translate customer reviews into another language

• To predict the sentiment of the next customer review

• To identify the sentiment of a customer review

• To convert customer reviews to a standard format

Given the scenario, "Rohan is playing in the park," what would be the output after tokenization?

• "rohan is playing in the park"

• ["Rohan playing park"]

• ["rohan", "is", "play", "in", "the", "park"]

• ["Rohan", "is", "playing", "in", "the", "park"]

In a research paper, why is it important to remove stop words from the text?

• To eliminate common but less meaningful words

• To convert text to a different format

• To enhance text readability

• To ensure all words are spelled correctly

Why is lowercasing often performed during text pre-processing?

• To ensure consistency by treating "Language" and "language" as the same word

• To remove all numerical values from the text

• To reduce the dimensionality of the text data

• To make the text grammatically correct

Which of the following is not typically a part of the text pre-processing pipeline?

• Lowercasing

• Stop Words Removal

• Sentiment Analysis

• Text Tokenization