Microsoft Azure AI Fundamentals Natural Language Processing 2 — Questions and Answers
Question 1: What does the term 'tokenization' mean in the context of NLP?
- Encrypting text data for security
- Breaking text into individual words or subword units (Correct answer)
- Translating text into a numeric format
- Removing stop words from a sentence
Correct answer: Breaking text into individual words or subword units
Tokenization is the process of splitting text into smaller units called tokens, which are typically words or subword pieces.
Question 2: Which Azure feature allows you to extract structured information from forms and invoices?
- Azure AI Language key phrase extraction
- Azure AI Document Intelligence (Form Recognizer) (Correct answer)
- Azure Translator
- Azure AI Speech
Correct answer: Azure AI Document Intelligence (Form Recognizer)
Azure AI Document Intelligence (formerly Form Recognizer) uses AI to extract structured data like fields and tables from documents and forms.
Question 3: What is the role of the Azure Translator service?
- Convert speech to text
- Translate text between over 100 languages in real time (Correct answer)
- Analyze sentiment of customer messages
- Extract entities from documents
Correct answer: Translate text between over 100 languages in real time
Azure Translator provides real-time text translation across more than 100 languages using neural machine translation models.
Question 4: In Azure AI Language, what is Conversational Language Understanding (CLU) used for?
- Generating spoken audio from text
- Training models to predict user intents from conversational input (Correct answer)
- Detecting objects in images
- Monitoring model drift in production
Correct answer: Training models to predict user intents from conversational input
CLU enables developers to build models that classify user utterances into intents and extract entities, powering conversational apps and bots.
Question 5: Which NLP concept describes the multiple meanings a single word can have depending on context?
- Tokenization
- Lemmatization
- Lexical ambiguity (Correct answer)
- Stemming
Correct answer: Lexical ambiguity
Lexical ambiguity refers to the phenomenon where a word has multiple possible meanings that must be resolved using surrounding context.
Question 6: Which Azure AI Language feature identifies relationships between named entities and links them to well-known references like Wikipedia?
- Sentiment analysis
- Key phrase extraction
- Entity linking (Correct answer)
- Language detection
Correct answer: Entity linking
Entity linking disambiguates entities found in text by linking them to entries in a knowledge base such as Wikipedia.
Microsoft Azure AI Fundamentals Natural Language Processing 2
What does the term 'tokenization' mean in the context of NLP?