NLP and Text Pre-processing Quiz

What is the primary role of NLP in technology?

• To enable machines to understand and interact using human languages

• To create new programming languages

• To convert human languages into binary code

• To translate computer languages into human languages

Why is text pre-processing important in NLP?

• It helps in creating new languages

• It increases the size of the dataset

• It transforms text into a format that is easier for models to process

• It adds complexity to the text

What does tokenization achieve in text pre-processing?

• It translates text into another language

• It breaks down text into individual words or tokens

• It removes all punctuation from the text

• It converts text into a list of sentences

What is the purpose of case normalization?

• To convert all text to uppercase

• To convert all text to lowercase

• To remove all numbers from the text

• To add punctuation to the text

What are stop words in the context of NLP?

• Words that are always capitalized

• Words that are used to stop a sentence

• Commonly used words that are filtered out because they carry little information

• Words that are essential for understanding the text

How does removing stop words benefit NLP models?

• It increases the complexity of the text

• It makes the text more colorful

• It adds more words to the text

• It reduces the text size and focuses on more informative words

What is the main goal of stemming in text pre-processing?

• To add prefixes to words

• To convert words into their past tense

• To reduce words to their root form

• To translate words into another language

How does lemmatization differ from stemming?

• Lemmatization adds suffixes to words

• Lemmatization removes all vowels from words

• Lemmatization reduces words to their dictionary form

• Lemmatization converts words into their plural forms

Which of the following is not a text pre-processing technique?

• Stop word removal

• Image resizing

• Case normalization

• Tokenization

What is the result of applying stemming to a word?

• A shortened form that may not be a real word

• A longer version of the word

• A translation of the word

• A completely unrelated word