Named Entity Recognition Services

Improve the speed your organization uncovers actionable insights from text with named entity recognition. MarsCrowd’s global resource team is ready to help you train your AI to accurately identify entities within text.

Named Entity Recognition

What is Named Entity Recognition?

Named entity recognition (NER) is a machine’s ability to extract entities from text. It takes unstructured data and is able to pull out the information you’ve trained it to extract. This allows your business to take a large text dataset and pull out the most important aspects of it quickly.

Why MarsCrowd?

A Crowd of

Trained Specialists

A Crowd of


A Crowd of

In-House Linguists

Named Entity Recognition in Action

When our Crowd provides named entity recognition services, you can expect a seamless process for delivery. NER projects are broken down into 5 general steps from the collection of data all the way to delivery. The process looks something like the model below:


Training of

classification model

Text Data Collection for Machine Learning Process

Text data collection

Design of

feature extractors

Performance evaluation & visualization

How Does Named Entity Recognition Work?

Intent classification is a sub-set of natural language processing with the goal of assigning intent to pieces of text. This is done through the training of machine learning models. There are two foundational steps: collecting enough of the relevant data and then labeling that data accurately. By using your specific customer goals as intent classifiers, our Crowd can annotate every piece of text to assign the proper intent.
In the end, the model you train and feed data into is able to produce actionable insights about the intent people have regarding your product or service. The nature of this information can be used to take your business to the next level by being able to respond to your audience in near-real time. The choice is yours on whether or not you want to unlock somthing so potentially powerful.

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