Glossary

Named Entity Recognition (NER)

An NLP technique enabling AI to automatically identify and categorise people, organisations, products, and locations in text.

Definition

What this term means

An NLP technique that enables AI systems to automatically identify, extract, and categorise named entities, such as people, organisations, locations, products, and dates, from unstructured text. NER is a foundational capability that allows AI models to understand who and what is being discussed in any piece of content, and to connect those entities to their knowledge base.

Why it matters

The business impact

NER determines whether AI systems can accurately identify your brand in the content they process. If your brand name is ambiguous, inconsistently used, or easily confused with common words, NER systems may fail to recognise it, meaning your brand is overlooked in AI outputs. Clear, consistent brand naming and contextual cues improve NER accuracy and ensure your brand is correctly attributed.

Used in context

How you might use this term

A brand called 'Apex' was being confused with dozens of unrelated entities by AI NER systems. By consistently co-locating their brand name with their industry ('Apex Financial Solutions') and using structured data to disambiguate, they improved NER accuracy by 75% across major AI platforms.
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