11. 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 Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option D No explanation is given for this question Let's Discuss on Board
12. 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 Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option D No explanation is given for this question Let's Discuss on Board
13. 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 Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option C No explanation is given for this question Let's Discuss on Board
14. 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 Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option C No explanation is given for this question Let's Discuss on Board
15. 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 Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option B No explanation is given for this question Let's Discuss on Board
16. 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 Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option B No explanation is given for this question Let's Discuss on Board
17. 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) Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option D No explanation is given for this question Let's Discuss on Board
18. 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 Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option A No explanation is given for this question Let's Discuss on Board
19. 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 Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option B No explanation is given for this question Let's Discuss on Board
20. 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 Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option C No explanation is given for this question Let's Discuss on Board
