Natural Language Processing Flashcards
6 cards from real Microsoft Azure AI Fundamentals practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 6 Natural Language Processing flashcards as text
What does the term 'tokenization' mean in the context of NLP?
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.
Which Azure feature allows you to extract structured information from forms and invoices?
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.
What is the role of the Azure Translator service?
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.
In Azure AI Language, what is Conversational Language Understanding (CLU) used for?
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.
Which NLP concept describes the multiple meanings a single word can have depending on context?
Answer: Lexical ambiguity
Lexical ambiguity refers to the phenomenon where a word has multiple possible meanings that must be resolved using surrounding context.
Which Azure AI Language feature identifies relationships between named entities and links them to well-known references like Wikipedia?
Answer: Entity linking
Entity linking disambiguates entities found in text by linking them to entries in a knowledge base such as Wikipedia.