Field Content

Identification Analysis Definition

The Field Content identification analysis definition supports identification of global and locale specific data. The table below describes those elements that are specific to this locale. For a description of elements that are common across all locales, see the Field Content Identification Analysis Definition section in the Identification Analysis Definitions documentation.

Field Content
Description

The Field Content identification analysis definition identifies the type of data that is represented by a string.
Possible Outputs

BANK ACCOUNT NUMBER
CITY
CITY-STATE/PROVINCE-POSTAL CODE
COUNTRY
CURRENCY
DATE
DATE/TIME
DELIVERY ADDRESS
E-MAIL
EMPTY
FAMILY NAME
FULL ADDRESS
GEOGRAPHICAL POINT
GIVEN NAME
IBAN
INDIVIDUAL
MONTH
NETWORK ADDRESS
ORGANIZATION
ORGANIZATION ID
PAYMENT CARD NUMBER
PHONE
POSTAL CODE
SOCIAL SECURITY NUMBER
UNKNOWN
URL
VEHICLE REGISTRATION
Default Identity UNKNOWN
Examples Input Output
Herr Håvard Sandvik INDIVIDUAL
Helge Bull Gjertsen, Sr INDIVIDUAL
L C Skog INDIVIDUAL
Morten Riis-Andersen INDIVIDUAL
Bente Irene Oterholm Nielsen INDIVIDUAL
Hr. og Fru Jørgensen INDIVIDUAL
Hans & Grete Andersen INDIVIDUAL
Ørnulf GIVEN NAME
Anne-Lise GIVEN NAME
Ingvaldsen FAMILY NAME
Hallingskog-Hultin FAMILY NAME
Bertel O. Steen ORGANIZATION
Hennes & Mauritz ORGANIZATION
H H Entreprenør ORGANIZATION
Transocean Offshore (North Sea) Ltd ORGANIZATION
BNP Paribas S.A. Norway Branch ORGANIZATION
KPMG ORGANIZATION
Postbox 879, Sentrum Nedre Vollgt. 4, 0104 Oslo FULL ADDRESS
Otto Nielsens vei 12 DELIVERY ADDRESS
Postboks 847 DELIVERY ADDRESS
6460 Eidsvåg i Romsdal CITY-STATE/PROVINCE-POSTAL CODE
Stavanger CITY
5008 POSTAL CODE
+47 930 64 211 PHONE
31 12 31 12 PHONE
050403 93473 SOCIAL SECURITY NUMBER
UZ-77353 VEHICLE REGISTRATION
6350 05 14347 BANK ACCOUNT NUMBER
918014950 ORGANIZATION ID
Remarks

Some data has the potential for ambiguity. When conflicts occur, this definition uses the following priorities in this order to produce more accurate results when aggregating over a column of data:

  1. CURRENCY
  2. ORGANIZATION
  3. MONTH
  4. INDIVIDUAL
  5. CITY
  6. COUNTRY
  7. FAMILY NAME
  8. GIVEN NAME