Retrieval, Memory & Knowledge

Entity Extraction

Automatically identifying people, places, organisations, and dates in text.

Definition

Entity extraction (part of named entity recognition) is the process of automatically identifying and classifying specific types of information in text — names, organisations, locations, dates, financial figures, contract terms, and more. LLMs are highly capable at this task and can be instructed to extract structured data from unstructured documents. For businesses that process large volumes of documents, entity extraction can automate significant amounts of manual data entry.

Why this matters for your business

Automating entity extraction from incoming contracts, invoices, and correspondence can reduce data entry costs substantially and improve data quality by eliminating transcription errors.

Related Terms

Structured Output

Instructing the AI to produce output in a specific format like JSON, a table, or a list.

Document QA

Using an LLM to answer questions based on specific uploaded documents.

Natural Language Processing (NLP)

The branch of AI that helps computers understand and generate human language.

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Disclaimer

This definition is provided for educational and informational purposes only. It represents a general explanation of a technical concept and does not constitute professional, technical, or investment advice. Artificial intelligence is a rapidly evolving field; terminology, techniques, and capabilities change frequently. Coaley Peak Ltd makes no warranty as to the accuracy, completeness, or currency of the information provided. Nothing on this page should be relied upon as the sole basis for commercial, technical, legal, or investment decisions without independent professional advice.

Document reference: ISO_webpage_knowledge-base_glossary_v1

Last modified: 29 March 2026

Knowledge Base·Retrieval, Memory & Knowledge·Entity Extraction