Named Entity Recognition
term_id: named_entity_recognition
Category: application_paradigms
Definition
Named Entity Recognition (NER) is a subtask of information extraction that locates and classifies named entities in text into pre-defined categories such as person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages, etc. It transforms unstructured text into structured data, enabling downstream applications like knowledge graph construction, search engine optimization, and automated document summarization by understanding the semantic roles of specific words.
Summary
A natural language processing task that identifies and classifies key information entities into predefined categories.
Key Concepts
- Entity typing
- Token classification
- Sequence labeling
- BiLSTM-CRF architectures
Use Cases
- Resume parsing
- Customer support intent detection
- Medical record analysis