Named Entity Recognition
Named entity recognition (NER) is an NLP technique that identifies and classifies key information in text into predefined categories such as names, dates, amounts, products, and locations.
In Depth
NER is the technology that extracts structured, actionable data from unstructured customer messages. When a customer writes 'I ordered the blue XL jacket on March 5th for $89.99 and it arrived at my London address damaged,' NER identifies 'blue XL jacket' as a product, 'March 5th' as a date, '$89.99' as a monetary amount, and 'London' as a location. This structured extraction allows AI agents to automatically look up the order, verify the purchase details, and initiate the appropriate workflow without asking the customer to repeat information.
In support operations, NER also powers features like automatic ticket tagging, PII detection and redaction (identifying and masking personal data), compliance monitoring (flagging mentions of regulated topics), and knowledge base article matching (connecting customer descriptions to relevant documentation).
Related Terms
Natural Language Processing
Natural Language Processing (NLP) is a branch of AI that enables computers to understand, interpret, and generate human language in a meaningful way.
Natural Language Understanding
Natural Language Understanding (NLU) is a subset of NLP focused on enabling machines to comprehend the meaning, intent, and context behind human language input.
Intent Detection
Intent detection is the process of identifying the purpose or goal behind a user's message, allowing AI systems to route requests and trigger appropriate actions.
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