NLP — core task?
Extract meaning from human language
Classical NLP pipeline — step?
Tokenization, morphology, syntax, semantics, pragmatics
Word embeddings — type?
Vector representations capturing similarity
NLP — definition?
Enables machines to interpret and generate human language.
Transformers — key feature?
Parallel processing with self-attention mechanisms.
Large Language Models — examples?
BERT, GPT, T5.
Static embeddings — limitation?
Limited polysemy handling, fixed meaning.
Tokenization — role?
Splits text into words or subword units.
Syntax parsing — purpose?
Builds sentence structure trees or dependencies.
Responsible NLP — concerns?
Bias, fairness, privacy, energy use.
Answer 9 questions on AI Language Interaction and Technologies.
1. What is the primary goal of natural language processing (NLP) in human–computer interaction?
2. Which step is NOT part of the classical NLP pipeline?
Go over the full study guide for AI Language Interaction and Technologies.
Read the study guide →Upload your class notes and Revizly writes your flashcards in about a minute.
Flashcard maker