An extraction system selects information such as names, dates, measurements or relationships from documents and maps it to defined fields. The result can support search, comparison or further analysis without requiring a person to reread every source for each question.
AI systems can help interpret varied layouts and wording, but extraction still requires evidence checks. Missing context, ambiguous tables and disconnected figures can produce incorrect fields, so important results should retain source references and be validated before downstream use.
ELI5
Imagine filling in a comparison table from several long reports. You look for the same facts in each report and place them under consistent column headings.
For example, a research assistant can collect the stated temperature and test result from each experiment. A reviewer checks the original passages and leaves a field uncertain when the source does not establish its value.
How does extraction differ from summarization?
Extraction targets specified facts or relationships, while summarization produces a shorter account of the material's main ideas.
Can an extracted field be trusted automatically?
No. Source ambiguity and model mistakes remain possible, so important fields need traceable evidence and suitable validation.
