How to use Named Entity Recognition (NER) API with Python in 5 minutes?

How to use Named Entity Recognition (NER) API with Python in 5 minutes?

In this tutorial, you will learn how to use Named Entity Recognition (NER) API in 5 minutes using Python and Eden AI NER API. Eden AI provides an easy and developer-friendly API that allows you to detect named entities in texts.

What is Named Entity Recognition (NER) API? 

In the public sector, administrations are faced with a considerable number of documents to manage. These documents must be indexed and organised in such a way that information can be easily retrieved. In this context, NER, a technique based on machine learning and Natural Language Processing (NLP), is a particularly interesting solution. It allows the automatic extraction of information from textual documents as well as audio and video.

If you want to learn more about what NER can offer, check out our Top 10 NER APIs.

Looking for more tutorials? Here are a couple of walkthroughs on How to use NER with JavaScript and PHP

Getting Started with NER API

The first step to using NER API is to install Python's requests package, that will allow you to call Eden AI API.

Next, you'll need to install Python's JSON package in order to read and print the result of the API request.

How to Use NER API in Text with Python?

You are now ready to process text into Eden AI NER API. You can process NER in many languages. You can access the list of languages supported in our documentation here.

1. Get your NER API Key on Eden AI

To perform NER, you'll need to create an account on Eden AI for free. Then, you'll be able to get your API key direclty from the homepage with free credits offered by Eden AI.

Eden AI - Get your API key for FREE

2. Let’s Detect Named Entities (NER) in Text

Now that you have imported packages on Python and got your API key, you will be able to detect named entities in your text. With Eden AI, you can choose from a wide range of providers you want to use for NER. You can access NER providers available on Eden AI on our documentation here.

Here is the Python script you need to write on your notebook:

For example, we called two different NER engines. Eden AI API will then return in its JSON response results of those providers.

Once the request is done, you will be able to get the result with this print:

Here is an example of a NER API response:

Benefits of using NER API with Eden AI

Using Named Entity Recognition with Eden AI API is quick and easy.

Multiple AIs in one API - Eden AI

Save time and cost

We offer a unified API for all providers: simple and standard to use, with a quick switch between providers and an access to the specificic features of each provider

Easy to integrate

The JSON output format is the same for all suppliers thanks to Eden AI's standardisation work. The response elements are also standardised thanks to Eden AI's powerful matching algorithms.


With Eden AI you have the possibility to integrate a third party platform: we can quickly develop connectors. To go further and customize your NER request with specific parameters, check out our documentation.

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