What is the primary use of a "corpus" in Natural Language Processing (NLP)?
A. To perform machine translation
B. To store and analyze a collection of texts
C. To identify the sentiment of a text
D. To generate random text
Which NLP technique involves assigning a numerical value to each word in a document, typically representing word frequency or importance?
A. Named Entity Recognition
B. Sentiment Analysis
C. Part-of-Speech Tagging
D. Term Frequency-Inverse Document Frequency (TF-IDF)
In NLP, what does "TF-IDF" stand for?
A. Term Frequency-Inverse Document Frequency
B. Text Feature Indexing-Inverted Dictionary Format
C. Token Frequency-Inverted Data Field
D. Term Frequency-Information Document Format
Which NLP task involves determining the structure of a document, such as extracting headings, paragraphs, and sections?
A. Named Entity Recognition
B. Document Summarization
C. Part-of-Speech Tagging
D. Machine Translation
What is the primary goal of Document Summarization in NLP?
A. To recognize and classify named entities (e.g., names, locations)
B. To identify the sentiment of a text
C. To generate a concise and coherent summary of a document
D. To perform tokenization
What is the primary goal of Machine Translation in NLP?
A. To recognize and classify named entities (e.g., names, locations)
B. To identify the sentiment of a text
C. To perform tokenization
D. To translate text from one language to another
Which NLP task involves converting text from one language to another while preserving its meaning and context?
A. Named Entity Recognition
B. Sentiment Analysis
C. Part-of-Speech Tagging
D. Machine Translation
What is the purpose of "lemmatization" in NLP?
A. To group words into topics
B. To split text into individual words or tokens
C. To reduce words to their base or dictionary form
D. To recognize named entities
Which NLP technique involves tagging each word in a text with its corresponding part of speech (e.g., noun, verb, adjective)?
A. Named Entity Recognition
B. Sentiment Analysis
C. Part-of-Speech Tagging
D. Lemmatization
In the context of NLP, what does the acronym "NER" stand for?
A. Natural Entity Recognition
B. Named Entity Recognition
C. Normalized Entity Recognition
D. Named Entity Resampling
What is the primary purpose of Named Entity Recognition (NER) in NLP?
A. To identify the sentiment of a text
B. To recognize and classify named entities (e.g., names, locations)
C. To perform machine translation
D. To perform tokenization
What is the primary goal of Sentiment Analysis in NLP?
A. To recognize and classify named entities (e.g., names, locations)
B. To identify the sentiment of a text
C. To perform machine translation
D. To perform tokenization
Which NLP task involves determining the sentiment or emotional tone expressed in a piece of text, such as positive, negative, or neutral?
A. Named Entity Recognition
B. Sentiment Analysis
C. Part-of-Speech Tagging
D. Machine Translation
What is the purpose of "tokenization" in NLP?
A. To group words into topics
B. To split text into individual words or tokens
C. To translate text from one language to another
D. To recognize named entities
Which NLP technique involves reducing words to their root form by removing suffixes and prefixes, even if the result is not a valid word?
A. Named Entity Recognition
B. Sentiment Analysis
C. Part-of-Speech Tagging
D. Stemming
What is the primary goal of Natural Language Processing (NLP)?
A. To generate random text
B. To understand, interpret, and generate human language
C. To analyze only written text
D. To automate data visualization
Which NLP task involves determining the grammatical structure of a sentence, including its parts of speech (e.g., noun, verb, adjective)?
A. Named Entity Recognition
B. Sentiment Analysis
C. Part-of-Speech Tagging
D. Machine Translation
Which of the following is a common preprocessing step in NLP for converting text to a uniform format by removing punctuation, capitalization, and stopwords?
A. Stemming
B. Tokenization
C. Lemmatization
D. Normalization
In the context of NLP, what does the acronym "POS" stand for?
A. Part-of-Speech
B. Positive Output
C. Plain Old Search
D. Preprocessed Object Store
Which NLP technique involves converting words into their base or dictionary form, reducing them to their root form?
A. Named Entity Recognition
B. Sentiment Analysis
C. Part-of-Speech Tagging
D. Lemmatization
