// Dynamic Entity Finder & NER Tool
Paste any block of text (articles, transcripts, banking offers, reports) to dynamically extract, highlight, and group all named entities across 15 distinct categories & sub-types — with contextual semantic parsing, occurrence counts, and structured dataset exports.
📝 Content Input
Dynamic Named Entity Extractor
Paste your text block on the left and click Extract & Group Entities.
// Grouped Entity Breakdown Table
Explore each detected entity name, category classification, total occurrence count, and context snippet.
| # | Entity Name ↕ | Category Type ↕ | Count ↕ | Share % | Context Snippet | Actions |
|---|
// 15-Category Named Entity Recognition Engine
Extract structured knowledge graphs from unstructured articles, financial offers, transcripts, and marketing copy.
Context-Aware NLP Heuristics
Our multi-tier recognition engine uses contextual surrounding word windows to dynamically assign precise badges (Percentages, Credit Scores, Monetary Amounts, Tenures, Laws, Tech).
Interactive Filter & Jump
Click any category tab to view only People, Brands, Products, or Laws. Click entity rows to jump directly to their visual location in the text.
Exportable Datasets
Instantly export your entity extraction table into CSV or JSON formats for downstream LLM analysis, RAG pipelines, SEO auditing, or market research.