Quiz on Language Modeling and PoS Tagging

What is a Unigram Language Model primarily concerned with?

• Counting sentences in a text

• Analyzing sentence structure

• Counting words in corpora

• Identifying named entities

Which of the following is a technique used for smoothing in N-grams?

• Dependency Parsing

• Deleted Interpolation

• Word Segmentation

• Tokenization

What does PoS tagging stand for?

• Part-Of-Sentence tagging

• Position-Of-Speech tagging

• Phrase-Of-Sentence tagging

• Part-Of-Speech tagging

Which model is mentioned in relation to Natural Language Generation?

• Decision Trees

• Hidden Markov Models

• Neural Networks

• Support Vector Machines

What is the focus of Morphology in language processing?

• The structure of sentences

• The meaning of words

• The formation and structure of words

• The pronunciation of words

Which of the following is a common method for evaluating language models?

• Precision

• Perplexity

• Accuracy

• F1 Score

What is the primary purpose of Tokenization in Natural Language Processing?

• To translate text into another language

• To break text into smaller units

• To summarize a document

• To identify the sentiment of a text

Which algorithm is commonly used for text classification tasks?

• Linear Regression

• Naive Bayes

• K-Means Clustering

• Random Forest

What is the main advantage of using a Bigram Language Model over a Unigram Model?

• It is easier to implement

• It requires less computational power

• It considers the order of words

• It uses fewer training data

Which of the following techniques is used for Named Entity Recognition?

• Data Augmentation

• Clustering

• Rule-Based Systems

• Sentiment Analysis