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SAS Quality Knowledge Base for Contact Information 26

French Definitions

In the SAS Quality Knowledge Base, the French definitions are shared by all French-language locales. Shared French definitions are described below.

Case Definitions
Extraction Definitions
Gender Analysis Definitions

Identification Analysis Definitions

Match Definitions

Parse Definitions

Pattern Analysis Definitions

Standardization Definitions

Inherited Definitions

Case Definitions

Proper (Name)
Description The Proper (Name) case definition propercases names of individuals.
  Input Output
Examples MONSIEUR JEAN-JACQUES LANVIN Monsieur Jean-Jacques Lanvin
mme de la tour Mme de la Tour
JAN VAN DEN BRINK Jan van den Brink
Remarks Prepositions are lowercased.

 

Proper (Organization)
Description The Proper (Organization) case definition propercases organization names.
  Input Output
Examples Bnp Paribas BNP Paribas
La maison de lucy La Maison de Lucy
SNCF SNCF
Remarks Acronyms are uppercased, while prepositions are lowercased.

 

Upper (Legal Form)
Description The Upper (Legal Form) case definition uppercases organization legal forms.
  Input Output
Examples cie CIE
ei EI
gmbh GmbH
SPA SpA
Remarks The Upper (Legal Form) case definition is designed for use on the Legal Form token only. Legal forms are generally uppercased, but with exceptions like GmbH and SpA.

 

Upper (Organization)
Description The Upper (Organization) case definition uppercases Latin characters found in organization names.
  Input Output
Examples Bnp Paribas BNP PARIBAS
La Maison de Lucy LA MAISON DE LUCY
sncf SNCF
radin.com radin.com
Remarks Organization names are uppercased, unless they are web site names.

Extraction Definitions

None.

Gender Analysis Definitions

Name
Description The Name gender analysis definition determines the gender of a name.
Possible Outputs M
F
U
  Input Output
Examples Mme Anne Chaumont F
Marc Daverat M
Dr Weissmann U
Jean-Marie Weber M
Marie-Jean Weber F
Remarks  

Identification Analysis Definitions

Field Name
Description

The Field Name identification analysis definition identifies database column names.

Possible Outputs NAME
ORGANIZATION
ADDRESS
CITY
STATE/PROVINCE
POSTALCODE
COUNTRY
PHONE
EMAIL
DATE
UNKNOWN
URL
GENDER
MATCHCODE
PERSONAL_ID
ORGANIZATION_ID
GENERIC_ID
COUNTY
MARITAL_STATUS
  Input Output
Examples Company Name ORGANIZATION
NOM D'ENTREPRISE ORGANIZATION
Address ADDRESS
boite aux lettres ADDRESS
Telephone PHONE
Numero Telephone Mobile PHONE
Remarks

This definition is recommended to determine the type of data stored in a database column based on the name of the column.

 

Name/Organization
Description The Name/Organization identification analysis definition determines whether a string represents the name of an individual or an organization.
Possible Outputs NAME
ORGANIZATION
NAME/ORGANIZATION
UNKNOWN
  Input Output
Examples Monsieur Henri Dumont NAME
Henri Dumont SA ORGANIZATION
SNCF ORGANIZATION
Monsieur Rejany NAME
Monsieur Rejany, SOLVEO NAME/ORGANIZATION
Rejany UNKNOWN
Remarks  

Match Definitions

Field Name
Description The Field Name match definition generates match codes which can be used to cluster records containing database field names.
Max Length of Match Code 15 characters
  Input Cluster ID
Examples Company Name 0
NOM D'ENTREPRISE 0
boite aux lettres 1
Address 1
Telephone 2
Numero Telephone Mobile 2
Remarks

This definition should be used to find potential matches between database column names.

NoteNote: The results listed above reflect the default match sensitivity (85).

 

Name
Description The Name match definition generates match codes which can be used to cluster records containing names of individuals.
Max Length of Match Code 26 characters
  Input Cluster ID
Examples Anne Christin Chaumont 0
Anne Charlotte Chaumont 0
Docteur Anne Christin Chaumont 0
Remarks

NoteNote: The results listed above reflect the default match sensitivity (85).

 

Organization
Description The Organization match definition generates match codes which can be used to cluster records containing organization names.
Max Length of Match Code 35 characters
  Input Cluster ID
Examples La banque postale 0
Banque postale, la 0
La lyonnaise de banque 1
Remarks

NoteNote: The results listed above reflect the default match sensitivity (85).

Parse Definitions

Name
Description The Name parse definition parses names of individuals into a set of tokens.
Output Tokens Prefix
Given Name
Family Name
Suffix
Title/Additional Info
  Input Output Token Output
Example 1 Monsieur Jean Pierre Lacombe Prefix Monsieur
Given Name Jean Pierre
Family Name Lacombe
Suffix  
Title/Additional Info  
  Input Output Token Output
Example 2 M J Pierre Lacombe Jr, PDG Prefix M
Given Name J Pierre
Family Name Lacombe
Suffix Jr
Title/Additional Info PDG
  Input Output Token Output
Example 3 Mlle Floriane de la Tour, Directrice Ressources Humaines Prefix Mlle
Given Name Floriane
Family Name de la Tour
Suffix  
Title/Additional Info Directrice Ressources Humaines
Remarks  

 

Name (Global)
Description The Name (Global) parse definition parses names of individuals into a globally recognized set of tokens.
Output Tokens Prefix
Given Name
Middle Name
Family Name
Suffix
Title/Additional Info
  Input Output Token Output
Example 1 Monsieur Jean Pierre Lacombe Prefix Monsieur
Given Name Jean Pierre
Middle Name  
Family Name Lacombe
Suffix  
Title/Additional Info  
  Input Output Token Output
Example 2 M J Pierre Lacombe Jr, PDG Prefix M
Given Name J Pierre
Middle Name  
Family Name Lacombe
Suffix Jr
Title/Additional Info PDG
  Input Output Token Output
Example 3 Mlle Floriane de la Tour, Directrice Ressources Humaines Prefix Mlle
Given Name Floriane
Middle Name  
Family Name de la Tour
Suffix  
Title/Additional Info Directrice Ressources Humaines
Remarks The Middle Name token is not populated in this definition.

Parse definitions named with the Global keyword use a set of output tokens that is consistent across every locale. Results obtained from these definitions can be stored in the same database fields as the results obtained from definitions of the same name in other locales.

 

Name (Multiple Name)
Description The Name (Multiple Name) parse definition parses strings that contain the names of two individuals into a set of tokens.
Output Tokens Name 1
Name 2
  Input Output Token Output
Example 1 Valérie Brua et Marc Daudin Name 1 Valérie Brua
Name 2 Marc Daudin
  Input Output Token Output
Example 2 M et Mme Daudin Marc Name 1 M Marc Daudin
Name 2 Mme Daudin
  Input Output Token Output
Example 3 Valérie & Marc Daudin Name 1 Valérie Daudin
Name 2 Marc Daudin
Remarks  

 

Name/Organization
Description The Name/Organization parse definition parses names and organizations into a set of tokens.
Output Tokens Name
Organization
  Input Output Token Output
Example 1 Monsieur Jean Pierre Lacombe Name Monsieur Jean Pierre Lacombe
Organization  
  Input Output Token Output
Example 2 SNCF Name  
Organization SNCF
  Input Output Token Output
Example 3 Monsieur Jean Pierre Lacombe, SNCF Name Monsieur Jean Pierre Lacombe
Organization SNCF
Remarks  

 

Organization
Description The Organization parse definition parses organization names into a set of tokens.
Output Tokens Name
Legal Form
Site
Additional Info
  Input Output Token Output
Example 1 SOLVEO SA, Lyon Name SOLVEO
Legal Form SA
Site Lyon
Additional Info  
  Input Output Token Output
Example 2 SOLVEO, Lyon, Service Informatique Name SOLVEO
Legal Form  
Site Lyon
Additional Info Service Informatique
  Input Output Token Output
Example 3 SOLVEO Paris Name SOLVEO Paris
Legal Form  
Site  
Additional Info  
Remarks  

 

Organization (Global)
Description The Organization (Global) parse definition parses organization names into a set of tokens.
Output Tokens Name
Legal Form
Site
Additional Info
  Input Output Token Output
Example 1 SOLVEO SA, Lyon Name SOLVEO
Legal Form SA
Site Lyon
Additional Info  
  Input Output Token Output
Example 2 SOLVEO, Lyon, Service Informatique Name SOLVEO
Legal Form  
Site Lyon
Additional Info Service Informatique
  Input Output Token Output
Example 3 SOLVEO Paris Name SOLVEO Paris
Legal Form  
Site  
Additional Info  
Remarks Parse definitions named with the Global keyword use a set of output tokens that is consistent across every locale. Results obtained from these definitions can be stored in the same database fields as the results obtained from definitions of the same name in other locales.

Pattern Analysis Definitions

None.

Standardization Definitions

Country
Description The Country standardization definition standardizes country names.
  Input Output
Examples etats-unis États-Unis
GÉORGIE Géorgie
Remarks  

 

Country (ISO 2 Char)
Description The Country (ISO 2 Char) standardization definition standardizes country names into the ISO-3166 two-character designation.
  Input Output
Examples etats-unis US
GÉORGIE GE
Remarks  

 

Country (ISO 3 Char)
Description The Country (ISO 3 Char) standardization definition standardizes country names into the ISO-3166 three-character designation.
  Input Output
Examples etats-unis USA
GÉORGIE GEO
Remarks  

 

Name
Description The Name standardization definition standardizes names of individuals.
  Input Output
Examples Docteur Marc Weissmann Junior Dr Marc Weissmann, Jr
Mademoiselle Jacqueline DE LA SALLE, Directrice de centre Mlle Jacqueline de la Salle, Directrice de Centre
Remarks  

 

Organization
Description The Organization standardization definition standardizes organization names.
  Input Output
Examples Secam Entreprise Individuelle, alby Secam EI, Alby
Kaufman and Broad SA Marseille Kaufman & Broad SA, Marseille
Remarks  

 

Organization (Upper)
Description The Organization (Upper) standardization definition standardizes and uppercases organization names.
  Input Output
Examples Secam Entreprise Individuelle, alby SECAM EI, ALBY
Kaufman and Broad SA Marseille KAUFMAN & BROAD SA, MARSEILLE
radin.com radin.com
Remarks The Organization (Upper) standardization definition uppercases all organization names except those that are website names.

Inherited Definitions

In addition to the definitions listed on this page, all French-language locales also inherit all Global definitions.