AI GlossaryNamed Entity Recognition (NER)ENTRY — Natural Language Processing
[Natural Language Processing]
Named Entity Recognition (NER).
Identifying and classifying named entities in text into categories like person, organization, location.
In-depth explanation
01NER is a sequence labeling task that extracts and classifies entities from unstructured text. Common entity types include PERSON, ORGANIZATION, LOCATION, DATE, and MONEY. NER is fundamental to information extraction, question answering, and knowledge graph construction. Modern NER uses transformer-based models for state-of-the-art performance.
Examples
02EX. 01
"Apple was founded by Steve Jobs" → PERSON: Steve Jobs, ORG: Apple
More in Natural Language Processing
0301BERTBidirectional Encoder Representations from Transformers, a pre-trained language model for NLP tasks.02Natural Language Processing (NLP)The field of AI focused on enabling computers to understand, interpret, and generate human language.03Sentiment AnalysisDetermining the emotional tone or opinion expressed in text, typically positive, negative, or neutral.04TokenizationBreaking text into smaller units (tokens) such as words, subwords, or characters.05Word EmbeddingDense vector representations of words that capture semantic meaning and relationships.
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