Intermediate · NLP

Entity Recognition (Named Entity Recognition)

Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.

TL;DR. Identifying and classifying named entities in text into predefined categories like names, dates, or locations.

Technical Definition

Identifying and classifying named entities in text into predefined categories like names, dates, or locations.

How it works

Entity Recognition, often called NER, is vital for extracting specific and structured information from unstructured text. For example, in 'I want to fly to Paris on Tuesday', 'Paris' would be tagged as a 'city' and 'Tuesday' as a 'date'. This structured data is then used for slot filling and deeper understanding in conversational AI.

Related Concepts

• Natural Language Understanding (NLU) — The ability of a computer program to understand human language as it is spoken or written.
• Slot Filling — The process of extracting specific pieces of information (slots) from a user's utterance needed to fulfill an intent.