Data Extraction
Automatically pulling structured information from unstructured documents.
Definition
Data extraction is the process of automatically identifying and pulling specific pieces of information from unstructured or semi-structured documents. This includes extracting entities (names, dates, amounts), relationships between entities, and structured data from tables and forms. Modern AI-powered extraction understands context and can extract data even when formatting varies significantly between documents.
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Related terms
Intelligent Document Processing (IDP)
AI-powered automation that extracts, classifies, and processes data from documents.
Named Entity Recognition (NER)
Identifying and classifying named entities like people, organisations, and dates in text.
Document Parsing
Converting documents into structured, machine-readable data.
More in Document Processing
Document Classification
Automatically categorising documents by type, topic, or purpose.
Intelligent Document Processing (IDP)
AI-powered automation that extracts, classifies, and processes data from documents.
Document Parsing
Converting documents into structured, machine-readable data.
OCR (Optical Character Recognition)
Technology that converts images of text into machine-readable text.
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Understanding the terminology is the first step. See how Conductor applies these concepts to solve real document intelligence challenges.
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