Field Match (Value Extractor): Difference between revisions

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Revision as of 10:38, 28 August 2024

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This article is a stub. It contains minimal information on the topic and should be expanded.

Field Match is a Value Extractor that matches the value stored in a previously-extracted variables Data Field or view_column Data Column.

This article is a placeholder at the moment. For now please visit the Field Match section of the Value Reader article.

Glossary

Data Column: view_column Data Columns represent columns in a table extracted from a document. They are added as child nodes of a table Data Table. They define the type of data each column holds along with its data extraction properties.

  • Data Columns are frequently referred to simply as "columns".
  • In the context of reviewing data in a Data Viewer, a single Data Column instance in a single Data Table row, is most frequently called a "cell".

Data Field: variables Data Fields represent a single value targeted for data extraction on a document. Data Fields are created as child nodes of a data_table Data Model and/or insert_page_break Data Sections.

  • Data Fields are frequently referred to simply as "fields".

Extract: export_notes Extract is an Activity that retrieves information from folder Batch Folder documents, as defined by Data Elements in a data_table Data Model. This is how Grooper locates unstructured data on your documents and collects it in a structured, usable format.

Extractor Type:

Field Match: Field Match is a Value Extractor that matches the value stored in a previously-extracted variables Data Field or view_column Data Column.

Value Reader: quick_reference_all Value Reader nodes define a single data extraction operation. Each Value Reader executes a single Value Extractor configuration. The Value Extractor determines the logic for returning data from a text-based document or page. (Example: Pattern Match is a Value Extractor that returns data using regular expressions).

  • Value Readers are can be used on their own or in conjunction with pin Data Types for more complex data extraction and collation.