Named Entity Recognition

We assist companies of all sizes to ensure accuracy and diversity in their data 50% more quickly than typical methods within the standard 12 categories, and also with regards to any custom requirements your project might demand.

Named Entity Reconition

Named Entity Recognition (NER) is a key task of information extraction that identifies and classifies specified entities mentioned in an unstructured body of text into established categories. ​

Where we help

NER is explicitly useful for improving day-to-day life via automatic task creation. For example, when you ask your voice assistant to set an alarm tomorrow at 7am, or when you ask your smart home to dim your lights in the evening, you can be sure that NER was behind the scenes at work. Due to the vast array of potential situations here, a large amount of diverse data is required to train the algorithm properly.

In commercial uses it can be used in real-time to process social media discussions to provide insights into how people are viewing your brand right now, allowing you to react to it in real-time.
It is also used to predict demand by monitoring how people are talking about different topics, allowing e-commerce and finance platforms to predict velocity more accurately. The accuracy of the data used to train the systems has a direct impact on the accuracy of the systems themselves.

The final use case where we see NER frequently is when it comes to education and search. NER algorithms allow for a more accurate linking of information between different entities to make search results more precise. This requires again a large corpus of very accurate data.

How we help

We can assist you to ensure accuracy and diversity in your NER data 50% more quickly than typical methods within the standard 12 categories and also with regards to any custom requirements your project might demand.

Source your data from our diverse group of over 10 million people around the globe. Generate new data relevant to your project requirements or similar to your existing data examples.

Gain 10% higher accuracy than the market-leading competitor for your diverse NER labeling tasks. Benefit from 3-5 humans verifying each data point at no extra cost.

Serve multiple languages at once and ensure 100% compliance with the world’s strictest security protocol.

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We’ve completed standalone & end-to-end machine learning projects for both small and enterprise-size companies across the world.
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