Glossary
Pulling specific data points — like dates, names, or order numbers — out of a user's message.
Entity extraction (also called named entity recognition) is the NLP task of identifying and pulling out specific pieces of information from text. Examples include a phone number, a city, a product SKU, an appointment date, or a currency amount.
While intent recognition answers 'what does the user want', entity extraction answers 'with what details'. Together they let a bot act: book the right slot, look up the right order, or send the right product.
Reliable entity extraction reduces back-and-forth by capturing the data needed to complete a task in a single message.
It lets automation complete tasks in fewer steps by capturing the exact details it needs from natural conversation.
Defuser AI extracts order numbers, dates and contact details from chats to power instant lookups — see WhatsApp order tracking.
Pulling specific data points — like dates, names, or order numbers — out of a user's message.
It lets automation complete tasks in fewer steps by capturing the exact details it needs from natural conversation.
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