---
title: Extract Named Entities from Text API
slug: extract-named-entities
url: https://apyhub.com/dosvak/service/extract-named-entities
provider: Dosvak LLC
categories: [Artificial Intelligence]
tags: [named-entity-recognition, nlp, text-analysis, entity-extraction, natural-language-processing]
auth: api_key
---

# Extract Named Entities from Text API

Extract people, organisations, locations, and misc entities from short text. Returns offsets and confidence scores for UI highlighting and NLP pipelines.

## Endpoints

| Method | Path | Description | Atoms |
| --- | --- | --- | --- |
| POST | `` | What it does Extracts named entities from the input text and returns the original text along with a… | 10 |

## About

## What it does
Named Entity Extraction identifies people, organisations, locations, and miscellaneous entities in text, and returns each match with character offsets.

Send a `text` string in the request body, and you get the original text back along with an `entities` array. Each entity includes the extracted `word`, its `type` (`PER`, `ORG`, `LOC`, or `MISC`), `start` and `end` offsets, and a confidence `score`. The input text is limited to 512 tokens, so it is designed for short passages, snippets, and document segments rather than full-length files.

Use Named Entity Extraction when you need to index articles, route support tickets, enrich content metadata, or prepare text for downstream NLP steps. The offsets make it easier to highlight entities in a UI, map results back to source text, or combine extraction with other text-processing logic.

This endpoint is a good fit for applications that need lightweight entity recognition without building and maintaining their own NLP pipeline.

## Usage

Authenticate with an ApyHub API key in the `apy-token` header.
Full docs and a live playground: https://apyhub.com/dosvak/service/extract-named-entities