Extract CNPJ

Verb: extractCnpj

Available from: <Enterprise>

Extracts CNPJs from plain text according to Language.

Syntax

extractCnpj --culture(Culture) --text(String) (List<String>)=values (String)=first (DataTable)=valuesmapping (Boolean)=success

Inputs

Script Designer Required AcceptedTypes Description
--culture Language Required Culture Language in which the defined text is written. Options:
  • en-US
  • pt-BR
  • pt-PT

  • The punctuation pattern changes according to the set language.
    --text Text Required Text Text from which to extract the CNPJ.

    Outputs

    Script Designer AcceptedTypes Description
    values Values List<Text> List of CNPJs extracted from text defined in Text
    first First value Text First CNPJ extracted from the text defined in Text.
    valuesmapping Values mapping Data Table Data table with parameter CNPJs Values.
    success Success Boolean True, it was successful in extracting; if not, returns False.

    Example

    Set Language to English (United States) to extract CNPJs from alleged clients.

    defVar --name cnpjsText --type String --value "Customer 1, CNPJ: 65.602.445/0001-97\r\nCustomer 2, CNPJ: 71.634.611/0001-30\r\nCustomer 3, CNPJ: 53.105.504/0001-32"
    defVar --name cnpjsList --type List --innertype String
    defVar --name firstValue --type String
    defVar --name success --type Boolean
    extractCnpj --culture en-US --text "${cnpjsText}" cnpjsList=values firstValue=first success=success
    logMessage --message "CNPJs List: ${cnpjsList}\r\nFirst CNPJ found: ${firstValue}\r\nSuccess:  ${success}" --type "Info"
    // Result:
    // CNPJs List: [65.602.445/0001-97,71.634.611/0001-30,53.105.504/0001-32]
    // First CNPJ found: 65.602.445/0001-97
    // Success:  True
    

    Remarks

    CNPJ is an identification number of brazilian companies. Can also be called National Register of Legal Entities. It would be the equivalent of a Registration Number (RN) in the US.

    See Also

  • Answer Question
  • Boolean Extract
  • Classify Text
  • Extract Address
  • Extract CPF
  • Extract Date
  • Extract E-mail Address
  • Extract Intent
  • Extract Monetary Value
  • Extract Named Entities
  • Extract Numbers
  • Extract Phone Number
  • Extract Quantity
  • Extract Time Span
  • Parse Sentences
  • Spell Checker
  • Summarize Text
  • Synonyms