Summarize this article with:
- Custom Named Entity Recognition (NER) API is a tool that enables users to build and deploy their own models for recognizing and extracting named entities from text such as names of people, organizations,...
- With a Custom NER API, users can train their models using their own labeled data, defining the specific entities they want to extract.
- The first step to getting started with Custom NER is to install Python's requests package, that will allow you to call Eden AI API.
- Developers can extract custom entities in text content with Python using a REST API that accepts standard inputs and returns structured JSON responses.
- The integration works with Python, JavaScript, PHP, and any HTTP-capable language with minimal setup.
In this tutorial, you will learn how to use Custom Named Entity Recognition API in 5 minutes with Python. Eden AI provides an easy and developer-friendly API that allows you to extract specific entities into text.
What is Custom Named Entity Recognition API?
Custom Named Entity Recognition (NER) API is a tool that enables users to build and deploy their own models for recognizing and extracting named entities from text such as names of people, organizations, locations, dates, or any other custom-defined categories.
With a Custom NER API, users can train their models using their own labeled data, defining the specific entities they want to extract. This customization allows for a more tailored and accurate identification of entities that are relevant to a particular domain, industry, or specific use case. Once the model is trained, the API provides an interface for developers to integrate the custom NER functionality into their applications or systems.
Get Started with Custom NER API
The first step to getting started with Custom NER 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 to be able to read and print the result of the API request.
How to extract specific entities in text with Python
You are now ready to process your file into Eden AI Custom NER API.
1. Get an Custom NER API Key on Eden AI
To perform Custom NER, you'll need to create an account on Eden AI for free. Then, you will be able to get your API key directly from the homepage with free credits offered by Eden AI.
2. Let’s extract specific entities in text
Now that you have imported packages on Python and got your API key, you will be able to extract specific entities in your texts. With Eden AI, you can choose from a wide range of different engines you want for Custom NER. You can access the list of Custom NER providers available on Eden AI on our documentation here.
Here is the Python script you need to write on your notebook:
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For example, we called two different Custom 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:
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Here is an example of a result for Custom NER task:
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Benefits of using Custom NER API with Eden AI
Using Custom Named Entity Recognition with Eden AI API is quick and easy.
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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 specific 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.
Customization
With Eden AI you have the possibility to integrate a third party platform: we can quickly develop connectors. To go further and customize your Custom NER request with specific parameters, check out our documentation.
Frequently Asked Questions (FAQ)
What do I need to extract custom entities in text content with Python??
You need an API key from your chosen AI provider. Eden AI lets you access multiple providers with a single key, removing the need for separate vendor accounts.
Which programming languages can I use?
Any language that supports HTTP requests works — Python, JavaScript, PHP, Ruby, Go, and more. Ready-to-use code snippets are available for the most common languages.
How long does the integration take?
Most developers complete a basic integration in under an hour using standardized API endpoints and ready-to-use code examples.
How do I handle errors and rate limits?
Implement exponential backoff for rate limit errors and use try-catch blocks for network failures. Eden AI's built-in fallback routing automatically redirects requests if a provider is unavailable.
Is the data I send secure and GDPR-compliant?
Check each provider's data processing agreement. Eden AI supports GDPR-compliant provider filtering and does not store or reuse your data.
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