FlowEngine Data Standardize & Clean icon

FlowEngine Data Standardize & Clean

Clean and transform data without code - deduplicate, format phones, normalize emails, and more

Extract From Text

AI-generated

Summary

Extract specified types of data such as emails, phone numbers, URLs, dates, amounts, hashtags, and mentions from a text field in input items.

Inputs

  • Text Field (required) — The name of the field containing the text to extract data from.
  • What to Extract (required) — The types of data to extract from the text, selectable from dates, emails, hashtags, mentions, monetary amounts, numbers, phone numbers, and URLs.
  • Output Prefix (required) — Prefix to prepend to the output fields containing extracted data (e.g., extracted_emails).
  • Options — Additional settings including case-insensitive field matching, whether to continue on failure, debug mode output, whether to skip unchanged items, and whether to track changes made.

Output shape

a list of items, each containing the original JSON plus additional fields for each requested data type with the extracted values arrays.

For each input item, the operation extracts the specified data types from the indicated text field and adds new fields to that item prefixed by the configured output prefix. If debug mode is enabled, a _debug field details the extraction process. If track changes is enabled, a _changes field records modifications. Items can be excluded if unchanged depending on options.

Examples

Example 1: Extract emails and phone numbers from a 'message' field, prefix output fields with 'found_'

Text Field: message; What to Extract: emails, phones; Output Prefix: found_

Discussion