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Named Entity Recognition (NER)

An NLP technique that identifies and classifies named entities in text, such as people, organizations, locations, dates, and monetary values.

How It Works

NER extracts structured information from unstructured text. Given "Tim Cook announced Apple's Q4 earnings of $89.5B on November 2, 2025 in Cupertino," NER identifies: Person (Tim Cook), Organization (Apple), Money ($89.5B), Date (November 2, 2025), Location (Cupertino). With LLMs, NER is done through prompting with structured output. Ask GPT-5-mini to extract entities and return JSON, and it handles complex, context-dependent cases that traditional NER systems miss. For high-volume processing, specialized models like SpaCy are faster and cheaper, but LLMs offer better accuracy on ambiguous or domain-specific text. In production, NER powers: data extraction from documents (invoices, contracts, resumes), search enhancement (index documents by entities for better retrieval), content linking (auto-link mentions of people or companies), compliance checking (detect PII in text), and knowledge graph construction (map relationships between entities). Combine NER with structured output mode for reliable, parseable results.

Common Use Cases

  • 1Invoice and receipt data extraction
  • 2Resume parsing
  • 3Legal document analysis
  • 4PII detection for compliance
  • 5Content enrichment and linking

Related Terms

Semantic Search

A search approach that finds results based on meaning rather than exact keyword matches, using embeddings to understand the intent behind queries.

Structured Output / JSON Mode

A feature that forces AI models to return responses in a specific format like JSON, ensuring parseable and type-safe outputs for programmatic use.

Natural Language Processing (NLP)

The branch of AI focused on enabling computers to understand, interpret, and generate human language in useful ways.

Sentiment Analysis

An NLP technique that determines the emotional tone of text, classifying it as positive, negative, neutral, or more granular emotions.

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