SAS Quality Knowledge Base for Contact Information 25
Definitions for the Czech, Czech Republic locale are described below.
Case Definitions
Gender Analysis Definitions
Identification Analysis Definitions
Match Definitions
Parse Definitions
Pattern Analysis Definitions
Standardization Definitions
Inherited Definitions
Proper (Address) | ||
---|---|---|
Description | The Case definition for Proper (Address) propercases addresses. | |
Input | Output | |
Examples | Nám. Svobody 5 181 | nám. Svobody 5 181 |
K.Ú. Vnorovice 6 | k.ú. Vnorovice 6 | |
Partyzánské Náměstí 1738/3,2 | Partyzánské náměstí 1738/3,2 | |
zahr.Kolonie Č. 8/1 | Zahr.kolonie č. 8/1 | |
čsl.armády 513 | ČSL.armády 513 | |
Remarks |
Proper (City - State/Province - Postal Code) | ||
---|---|---|
Description | The Case definition for Proper (City - State/Province - Postal Code) propercases address last line data. | |
Input | Output | |
Examples | 25246 VRANÉ NAD VLTAVOU | 25246 Vrané nad Vltavou |
33805 MÝTO V ČECHÁCH | 33805 Mýto v Čechách | |
Remarks |
Proper (Name) | ||
---|---|---|
Description | The Case definition for Proper (Name) propercases names of individuals. | |
Input | Output | |
Examples | LADISLAV HASTERMAN | Ladislav Hasterman |
p. j. ceslova | p. J. Ceslova | |
SL. Veronika Balážová | sl. Veronika Balážová | |
PHARMDR. Elena Jedináková | PharmDr. Elena Jedináková | |
JAN VAN DE BRINK | Jan van de Brink | |
Remarks |
Proper (Organization) | ||
---|---|---|
Description | The Case definition for Proper (Organization) propercases organization names. | |
Input | Output | |
Examples | AGENTÚRA NEXON s.r.o | Agentúra Nexon s.r.o |
ibm s.r.o. | IBM s.r.o. | |
DELL S.R.O. | Dell s.r.o. | |
gbh Trade s.r.o. | GBH Trade s.r.o. | |
AUTO A ČESKÁ REPUBLIKA | Auto A Česká republika | |
Remarks |
Birth Number | ||
---|---|---|
Description | The Gender Analysis definition for Birth Number determines the gender of a name based on birth number. | |
Possible Outputs | M F U |
|
Input | Output | |
Examples | 535731 - 456 | F |
936223/6147 | F | |
530731456 | M | |
010524/472 | M | |
128399/5616 | U | |
12.09.1956 | U | |
Remarks | This Gender Analysis definition for Birth Number requires the input data to be in the form of YYMMDDOOO, where YY is year of birth, MM is month of birth, DD is day of birth, and OOO is Order Number. Order Number can consist of three- or four-digits. Gender is determined by the month of birth. Values 01 through 12 are male, and values 51 through 62 are female. |
Name | ||
---|---|---|
Description | The Gender Analysis definition for Name determines the gender of a name. | |
Possible Outputs | M F U |
|
Input | Output | |
Examples | Anna-Mária Hrušková | F |
Katarína M | F | |
Zuzana | F | |
Jozef | M | |
Peter Zelený | M | |
B. L. | U | |
P K | U | |
Remarks |
Individual/Organization | ||
---|---|---|
Description | The Identification Analysis definition for Individual/Organization determines whether a string represents the name of an individual or an organization. | |
Possible Outputs | INDIVIDUAL ORGANIZATION UNKNOWN |
|
Input | Output | |
Examples | Dalibor Chadima | INDIVIDUAL |
Chadima, sro | ORGANIZATION | |
D.C. | UNKNOWN | |
Remarks |
Address | ||
---|---|---|
Description | The Address match definition generates match codes which can be used to cluster records containing addresses. | |
Max Length of Match Code | 30 characters | |
Input | Cluster ID | |
Examples | GEN. SVOBODU 691/19, po box 82 | 0 |
Generála Svobodu 691/15 POBOX 82 | 0 | |
Generála Svobodu 691 POBOX 82 | 0 | |
p.o. box 82, Generala Svobodu 691/155 | 0 | |
P O Box 82 | 1 | |
Generala Svobodu 691 | 2 | |
ul. Republiky 33 p box 50 | 3 | |
Ulica Republiky 33, box 50 | 3 | |
Nam. Republiky 33 pob 50/B | 3 | |
Ulica Republiky 33 | 4 | |
p box č. 50 | 5 | |
Remarks |
Note: The results listed above reflect the default match sensitivity (85). |
Address (PO Box Only) | ||
---|---|---|
Description | The Address (PO Box Only) match definition generates match codes which can be used to cluster records containing the PO Box portion of an address. | |
Max Length of Match Code | 15 characters | |
Input | Cluster ID | |
Examples | GEN. SVOBODU 691/19, po box 82 | 0 |
POBOX 82 | 0 | |
p.o. box 82, Generala Svobodu 691/155 | 0 | |
P O Box 82 | 0 | |
P O Box 83 | 1 | |
ul. Republiky 33 p box 50 | 2 | |
box 50 | 2 | |
pob 50/B | 2 | |
p box č. 50 | 2 | |
Remarks |
Note: The results listed above reflect the default match sensitivity (85). |
Address (Street Only) | ||
---|---|---|
Description | The Address (Street Only) match definition generates match codes which can be used to cluster records containing the street portion of an address. | |
Max Length of Match Code | 25 characters | |
Input | Cluster ID | |
Examples | GEN. SVOBODU 691/19, po box 82 | 0 |
Generála Svobodu 691/15 POBOX 82 | 0 | |
Generála Svobodu 691 POBOX 28 | 0 | |
Generala Svobodu 691/155 | 0 | |
Generala Svobodu 619 | 1 | |
ul. Republiky 33 p box 50 | 2 | |
Ulica Republiky 33, box 55 | 2 | |
Nam. Republiky 33/B | 2 | |
Remarks |
Note: The results listed above reflect the default match sensitivity (85). |
City | ||
---|---|---|
Description | The City match definition generates match codes which can be used to cluster records containing city names. | |
Max Length of Match Code | 15 characters | |
Input | Cluster ID | |
Examples | Rovensko pod Troska | 0 |
Rovensko pod Trosk. | 0 | |
Hrob | 1 | |
Remarks |
Note: The results listed above reflect the default match sensitivity (85). |
City - State/Province - Postal Code | ||
---|---|---|
Description | The City - State/Province - Postal Code match definition generates match codes which can be used to cluster records containing last line address information. | |
Max Length of Match Code | 17 characters | |
Input | Cluster ID | |
Examples | 61900 Brno 19 | 0 |
61900 BRNO | 0 | |
70200 Ostrava | 1 | |
Remarks |
Note: 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 | 20 characters | |
Input | Cluster ID | |
Examples | Jozef Klement | 0 |
Jožo Klement | 0 | |
Dodo Kliment | 0 | |
Adriana Hudecova | 1 | |
Adriána Hudecová | 1 | |
Jan v/d Brink | 2 | |
Jan van de Brink | 2 | |
Jan vd. Brink | 2 | |
Anna M. Sedláková | 3 | |
Anna Maria Sedláková | 3 | |
Anna-Maria Sedláková | 3 | |
Remarks |
Note: 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 | 40 characters | |
Input | Cluster ID | |
Examples | A-PROGRES S.R.O. | 0 |
A-Progres s.r.o. | 0 | |
CALIPSO v.o.s. | 1 | |
CALIPSO, veřejná obchodní společnost | 1 | |
CALIPSO | 1 | |
Asociácia Vydaveteľov a.s. | 2 | |
Asociáciu Vydavateľov a.s. | 2 | |
Asoc. Vydaveteľov a.s. | 2 | |
1. Garantovaná, a.s. | 3 | |
1st Garantovaná, a.s. | 3 | |
První Garantovaná, a.s. | 3 | |
2 DOMY, bytové družstvo | 4 | |
DVA DOMY, bytové družstvo | 4 | |
Remarks |
Note: The results listed above reflect the default match sensitivity (85). |
Phone | ||
---|---|---|
Description | The Phone match definition generates match codes which can be used to cluster records containing phone numbers. | |
Max Length of Match Code | 17 characters | |
Input | Cluster ID | |
Examples | 800 PRÁZDNINY | 0 |
800 772 936 | 0 | |
+420 226 026 424 | 1 | |
226 026 424 | 1 | |
+682 35664897 | 2 | |
+683 35664897 | 3 | |
224 310 808 Kl. 1234 | 4 | |
224 310 808 Kl. 5678 | 4 | |
228 866 624 | 5 | |
228 866 625 | 5 | |
228 866 636 | 6 | |
Remarks |
Note: The results listed above reflect the default match sensitivity (85). |
Postal Code | ||
---|---|---|
Description | The Postal Code match definition generates match codes which can be used to cluster records containing postal codes. | |
Max Length of Match Code | 15 characters | |
Input | Cluster ID | |
Examples | 61900 | 0 |
-61900 | 0 | |
15000 | 1 | |
Remarks |
Note: The results listed above reflect the default match sensitivity (85). |
Text | ||
---|---|---|
Description | The Text match definition generates match codes which can be used to cluster records containing general text strings. | |
Max Length of Match Code | 20 characters | |
Input | Cluster ID | |
Examples | počítač Dell | 0 |
POČÍTAČE DELL | 0 | |
Remarks |
Note: The results listed above reflect the default match sensitivity (85). |
Address | |||
---|---|---|---|
Description | The Parse definition for Address parses addresses into a set of tokens. | ||
Output Tokens | Building Name Building Number Street Extension Additional Info |
||
Input | Output | ||
Example 1 | Janovičky 11, P.O.BOX 36 | Building Name | |
Building Number | 11 | ||
Street | Janovičky | ||
Extension | P.O.BOX 36 | ||
Additional Info | |||
Input | Output | ||
Example 2 | 1. máje - Areál garáží | Building Name | |
Building Number | |||
Street | 1. máje | ||
Extension | |||
Additional Info | Areál garáží | ||
Input | Output | ||
Example 3 | Hájenka Metel - Nítovice 56 | Building Name | Hájenka Metel |
Building Number | 56 | ||
Street | Nítovice | ||
Extension | |||
Additional Info | |||
Remarks |
|
Address (Global) | |||
---|---|---|---|
Description |
The Address (Global) parse definition parses addresses into a globally recognized set of tokens. |
||
Output Tokens | Recipient Building/Site Street Extension PO Box Additional Info |
||
Input | Output | ||
Example 1 | Janovičky 11, P.O.BOX 36 | Recipient | |
Building/Site | |||
Street | Janovičky 11 | ||
Extension | |||
PO Box | P.O.BOX 36 | ||
Additional Info | |||
Input | Output | ||
Example 2 | 1. máje - Areál garáží | Recipient | |
Building/Site | |||
Street | 1. máje | ||
Extension | |||
PO Box | |||
Additional Info | Areál garáží | ||
Input | Output | ||
Example 3 | Hájenka Metel - Nítovice 56 | Recipient | |
Building/Site | Hájenka Metel | ||
Street | Nítovice 56 | ||
Extension | |||
PO Box | |||
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. | ||
The Address (Global) (v23) parse definition is now deprecated and will be removed in a future release of the QKB. The Address (Global) parse definition has been replaced with a copy of the Address (Global) (v23) definition which takes advantage of the new tokens and updated processing. If you changed your jobs to use Address (Global) (v23) it is suggested that you change them back. |
Address (Global) (v23) | |||
---|---|---|---|
Description |
The Address (Global) (v23) parse definition parses addresses into a globally recognized set of tokens. |
||
Output Tokens | Recipient Building/Site Street Extension PO Box Additional Info |
||
Input | Output | ||
Example 1 | Janovičky 11, P.O.BOX 36 | Recipient | |
Building/Site | |||
Street | Janovičky 11 | ||
Extension | |||
PO Box | P.O.BOX 36 | ||
Additional Info | |||
Input | Output | ||
Example 2 | 1. máje - Areál garáží | Recipient | |
Building/Site | |||
Street | 1. máje | ||
Extension | |||
PO Box | |||
Additional Info | Areál garáží | ||
Input | Output | ||
Example 3 | Hájenka Metel - Nítovice 56 | Recipient | |
Building/Site | Hájenka Metel | ||
Street | Nítovice 56 | ||
Extension | |||
PO Box | |||
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. | ||
The Address (Global) (v23) parse definition is now deprecated and will be removed in a future release of the QKB. The Address (Global) parse definition has been replaced with a copy of the Address (Global) (v23) definition which takes advantage of the new tokens and updated processing. If you changed your jobs to use Address (Global) (v23) it is suggested that you change them back. |
Birth Number | |||
---|---|---|---|
Description | The Parse definition for Birth Number parses birth numbers into a set of tokens. | ||
Output Tokens | Year of Birth Month of Birth Day of Birth Order Number Additional Info |
||
Input | Output | ||
Example 1 | 535731/456 | Year of Birth | 53 |
Month of Birth | 57 | ||
Day of Birth | 31 | ||
Order Number | 456 | ||
Additional Info | |||
Input | Output | ||
Example 2 | 9312236076 | Year of Birth | 93 |
Month of Birth | 12 | ||
Day of Birth | 23 | ||
Order Number | 6076 | ||
Additional Info | |||
Input | Output | ||
Example 3 | 084053/2524 | Year of Birth | 0 8 |
Month of Birth | 4 0 | ||
Day of Birth | 5 3 | ||
Order Number | 2 5 2 4 | ||
Additional Info | |||
Remarks | This Parse definition for Birth Number requires the input data to be in the form of YYMMDDOOO where YY is year of birth, MM is month of birth, DD is day of birth, and OOO is order number, which consists of three-digits if the birth year is before 1954 and four-digits if later than 1954. Month of birth values 01 through 12 are male and 51 through 62 are female. If the input string does not contain a correctly formatted birth number, the output has a NO SOLUTION parse result and is parsed based on the order of the input digits, as shown in Example 3, with spaces between the digits. The recommended procedure is to first determine if the input string can be parsed correctly, then apply parsing to the correctly formatted input data only. To determine if the formatting is correct, you can do either of the following: 1. In the Parse node, assign a Result Code field to capture whether a solution was found. Process output with NO SOLUTION results separately. 2. Run Gender Analysis on the input string using the Gender Analysis definition for Birth Number. Input strings that get U (Unknown) results cannot be parsed as a correctly formatted birth number. |
City - State/Province - Postal Code | |||
---|---|---|---|
Description | The Parse definition for City - State/Province - Postal Code parses address last line data into a set of tokens. | ||
Output Tokens | City Postal Code |
||
Input | Output | ||
Example | 15000 Praha 5 | City | Praha 5 |
Postal Code | 15000 | ||
Remarks |
City - State/Province - Postal Code (Global) | |||
---|---|---|---|
Description | The Parse definition for City - State/Province - Postal Code (Global) parses address last line data into a globally recognized set of tokens. | ||
Output Tokens | City State/Province Postal Code Additional Info |
||
Input | Output | ||
Example | 15000 Praha 5 | City | Praha 5 |
State/Province | |||
Postal Code | 15000 | ||
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. |
Name | |||
---|---|---|---|
Description | The Parse definition for Name parses names of individuals into a set of tokens. | ||
Output Tokens | Prefix Title Given Name Family Name Suffix Additional Info |
||
Input | Output | ||
Example | Mgr. Lukáš Dzurinda PhD. | Prefix | |
Title | Mgr. | ||
Given Name | Lukáš | ||
Family Name | Dzurinda | ||
Suffix | PhD. | ||
Additional Info | |||
Remarks |
Name (Global) | |||
---|---|---|---|
Description | The Parse definition for Name (Global) 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 | ||
Example | Mgr. Lukáš Dzurinda PhD. | Prefix | Mgr. |
Given Name | Lukáš | ||
Middle Name | |||
Family Name | Dzurinda | ||
Suffix | |||
Title/Additional Info | PhD. | ||
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. |
Name (Multiple Name) | |||
---|---|---|---|
Description | The Parse definition for Name (Multiple Name) parses strings that contain the names of two individuals into a set of tokens. | ||
Output Tokens | Name 1 Name 2 |
||
Input | Output | ||
Example 1 | Peter Kováč a Ivana Kováčová | Name 1 | Peter Kováč |
Name 2 | Ivana Kováčová | ||
Input | Output | ||
Example 2 | Peter a Ivana Kováčovci | Name 1 | Peter Kováčovci |
Name 2 | Ivana Kováčovci | ||
Input | Output | ||
Example 3 | Peter Tribula | Name 1 | Peter Tribula |
Name 2 | |||
Remarks | Czech family names use feminine, masculine, and plural variations. Because of this, strings containing multiple names should be standardized with the Standardization definition for Name (Multiple Name) before being processed with the Parse definition for Name (Multiple Name). Without standardization, the results of the parse might show incorrect family name variations for individual names (see Example 2). If only one name is present in the input, the first token is used. |
Organization | |||
---|---|---|---|
Description | The Parse definition for Organization parses organization names into a set of tokens. | ||
Output Tokens | Name Legal Form Site Additional Info |
||
Input | Output | ||
Example 1 | PRIMA ZDROJ S.R.O., NOVÁ PAKA | Name | PRIMA ZDROJ |
Legal Form | Ivana Kováčová | ||
Site | NOVÁ PAKA | ||
Additional Info | |||
Input | Output | ||
Example 2 | BP Trading s.r.o., Národní 42 | Name | BP Trading |
Legal Form | s.r.o. | ||
Site | |||
Additional Info | Národní 42 | ||
Input | Output | ||
Example 3 | Bobolovsky GmbH, Brno | Name | Bobolovsky` |
Legal Form | GmbH | ||
Site | Brno | ||
Additional Info | |||
Input | Output | ||
Example 4 | Ví & Kej-V.Kirilova a spol. spol. s r.o.-org.sl. | Name | Ví & Kej-V.Kirilova a spol. |
Legal Form | spol. s r.o. | ||
Site | |||
Additional Info | org.sl. | ||
Remarks |
Organization (Global) | |||
---|---|---|---|
Description | The Parse definition for Organization (Global) parses organization names into a globally recognized set of tokens. | ||
Output Tokens | Name Legal Form Site Additional Info |
||
Input | Output | ||
Example 1 | PRIMA ZDROJ S.R.O., NOVÁ PAKA | Name | PRIMA ZDROJ |
Legal Form | Ivana Kováčová | ||
Site | NOVÁ PAKA | ||
Additional Info | |||
Input | Output | ||
Example 2 | BP Trading s.r.o., Národní 42 | Name | BP Trading |
Legal Form | s.r.o. | ||
Site | |||
Additional Info | Národní 42 | ||
Input | Output | ||
Example 3 | Bobolovsky GmbH, Brno | Name | Bobolovsky |
Legal Form | GmbH | ||
Site | Brno | ||
Additional Info | |||
Input | Output | ||
Example 4 | Ví & Kej-V.Kirilova a spol. spol. s r.o.-org.sl. | Name | Ví & Kej-V.Kirilova a spol. |
Legal Form | spol. s r.o. | ||
Site | |||
Additional Info | org.sl. | ||
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. |
Phone | |||
---|---|---|---|
Description | The Parse definition for Phone parses phone numbers into a set of tokens. | ||
Output Tokens | Country Code Area Code Base Number Extension Line Type Additional Info |
||
Input | Output | ||
Example 1 | Pracovný Telefón: +420 2 81002 383 linka 4629 (noci ao víkendu) | Country Code | +420 |
Area Code | |||
Base Number | 2 81002 383 | ||
Extension | 4629 | ||
Line Type | Pracovný Telefón: | ||
Additional Info | (noci ao víkendu) | ||
Input | Output | ||
Example 2 | 5 4715 2700 (tel-fax) | Country Code | |
Area Code | |||
Base Number | 5 4715 2700 | ||
Extension | |||
Line Type | (tel-fax) | ||
Additional Info | |||
Input | Output | ||
Example 3 | 326 711 411 2 | Country Code | |
Area Code | |||
Base Number | 326 711 411 | ||
Extension | 2 | ||
Line Type | |||
Additional Info | |||
Input | Output | ||
Example 4 | +1 800-DATAFLUX | Country Code | +1 |
Area Code | |||
Base Number | 800-DATAFLUX | ||
Extension | |||
Line Type | |||
Additional Info | |||
Remarks |
Phone (Global) | |||
---|---|---|---|
Description | The Parse definition for Phone (Global) parses phone numbers into a globally recognized set of tokens. | ||
Output Tokens | Country Code Area Code Base Number Extension Line Type Additional Info |
||
Input | Output | ||
Example 1 | Pracovný Telefón: +420 2 81002 383 linka 4629 (noci ao víkendu) | Country Code | +420 |
Area Code | |||
Base Number | 2 81002 383 | ||
Extension | 4629 | ||
Line Type | Pracovný Telefón: | ||
Additional Info | (noci ao víkendu) | ||
Input | Output | ||
Example 2 | 5 4715 2700 (tel-fax) | Country Code | |
Area Code | |||
Base Number | 5 4715 2700 | ||
Extension | |||
Line Type | (tel-fax) | ||
Additional Info | |||
Input | Output | ||
Example 3 | 326 711 411 2 | Country Code | |
Area Code | |||
Base Number | 326 711 411 | ||
Extension | 2 | ||
Line Type | |||
Additional Info | |||
Input | Output | ||
Example 4 | +1 800-DATAFLUX | Country Code | +1 |
Area Code | |||
Base Number | 800-DATAFLUX | ||
Extension | |||
Line Type | |||
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. |
None.
Address | ||
---|---|---|
Description | The Standardization definition for Address standardizes addresses. | |
Input | Output | |
Examples | Za Kněžským hájkem parcela č. 1461/283 | za Kněžským Hájkem parc. č. 1461/283 |
2.ulice č. 78 | 2. ulice 78 | |
P.O.Box 6-Počáply | Počáply, P. O. Box 6 | |
Remarks |
Birth Number | ||
---|---|---|
Description | The Standardization definition for Birth Number standardizes birth numbers. | |
Input | Output | |
Examples | 9312236076 | 931223/6076 |
530731456 | 530731/456 | |
535731 - 456 | 535731/456 | |
93-62-23/6147 | 936223/6147 | |
Remarks | This Birth Number standardization definition requires the input data to be in the form of YYMMDDOOO where YY is year of birth, MM is month of birth, DD is day of birth, and OOO is order number, which consists of three-digits if the birth year is before 1954 and four-digits if later than 1954. Month of birth values 01 through 12 are male and 51 through 62 are female. The recommended procedure is to first determine if the input string is correctly formatted, then apply parsing to the correctly formatted input data only. To determine if the formatting is correct, do one of the following: 1. Parse the string using the Parse definition for Birth Number. Assign a Result Code Field in the Parse node in DataFlux Data Management Studio. Output with NO SOLUTION results is not formatted correctly and should be processed separately. 2. Run Gender Analysis on the input string using the Gender Analysis definition for Birth Number. Input strings that generate U (Unknown) results are not formatted correctly and should be processed separately. |
City | ||
---|---|---|
Description | The Standardization definition for City standardizes city names. | |
Input | Output | |
Examples | F.MÍSTEK | Frýdek-Místek |
Č BUD | České Budějovice | |
Remarks | Common city abbreviations are expanded into full names. |
City - State/Province - Postal Code | ||
---|---|---|
Description | The Standardization definition for City - State/Province - Postal Code standardizes address last line data. | |
Input | Output | |
Examples | 41501 Teplice v Č. | 41501 Teplice v Čechách |
16400 Praha - 619 | 16400 Praha 619 | |
Remarks |
Name | ||
---|---|---|
Description | The Standardization definition for Name standardizes names of individuals. | |
Input | Output | |
Examples | mgr. art Eva Janošová ArtD. | Mgr. art. Eva Janošová, ArtD. |
rndr. Július Kusala Csc. | RNDr. Július Kusala, CSc. | |
Peter Krempaský st. | Peter Krempaský, starší | |
Tatevik Avnikjan - Ciháková | Tatevik Avnikjan-Ciháková | |
Profesor Jirí Vácha | prof. Jirí Vácha | |
Prof. Ing. Jakub Mláka PhD | prof. Ing. Jakub Mláka, Ph.D. | |
Remarks |
Name (Multiple Name) | ||
---|---|---|
Description | The Standardization definition Name (Multiple Name) standardizes input data that contains two names. | |
Input | Output | |
Examples | Peter a Ivana Kováčovci | Peter Kováč a Ivana Kováčová |
Pan Peter a Paní Ivana Kováčovci | Pan Peter Kováč a Paní Ivana Kováčová | |
Ivan a Ivana Svobodové | Ivan Svoboda a Ivana Svobodová | |
Miroslav a Vladimíra Novotní | Miroslav Novotný a Vladimíra Novotná | |
P A & I K Kováčovci | P A Kováč a I K Kováčová | |
Peter Kováč, Ivana Kováčová | Peter Kováč a Ivana Kováčová | |
Remarks | This definition splits plural variations of Czech family names into individual feminine or masculine variations. It should be used to standardize strings containing multiple names before the Parse definition for Name (Multiple Name) is used to parse those strings. If the plural variation does not exist in the input string, the two names are simply separated, as shown in the final example. |
Organization | ||
---|---|---|
Description | The Standardization definition for Organization standardizes organization names. | |
Input | Output | |
Examples | Calipso Veřejná obchodní společnost | Calipso v.o.s. |
EAS EUROPE Společnost s ručením omezeným | EAS Europe s.r.o. | |
Omnia Motors, Akciová společnost | Omnia Motors a.s. | |
TATRACHEMA Výrobní družstvo | Tatrachema v.d. | |
H.B.T. Plast s r.o. | HBT Plast s.r.o. | |
ADIX, s.r.o. (Brno) | Adix s.r.o., Brno | |
Remarks |
Phone | ||
---|---|---|
Description | The Standardization definition for Phone standardizes phone numbers for domestic use. | |
Input | Output | |
Examples | 2 8 2 3 4 5 6 7 8 | 282 345 678 |
049/5500550 kl.1 | 495 500 550 x1 | |
055-7296 266 | (055) 7296266 | |
244222908 (večery a víkendy) | 244 222 908, Večery A Víkendy | |
0044 (0)20 12345000 | +44 2012345000 | |
Remarks |
Phone (Electronic) | ||
---|---|---|
Description | The Standardization definition for Phone (Electronic) standardizes phone numbers for automated calling systems. | |
Input | Output | |
Examples | Služ. Tel.: +420 2 81002 383 linka 4629 (středa a pátek) | +420281002383 |
225.993.111 | +420225993111 | |
+420 2 61 19 52 83 | +420261195283 | |
00420/281097111 | +420281097111 | |
800 PRÁZDNINY | +420800772936469 | |
+1 (919) 447-3000 | +19194473000 | |
Remarks |
Phone (with Country Code) | ||
---|---|---|
Description | The Standardization definition for Phone (with Country Code) standardizes phone numbers for international use. | |
Input | Output | |
Examples | 225 993 111 | +420 225 993 111 |
mobilní telefonní číslo: 607 978 806 | +420 607 978 806, Mobilní Telefonní Číslo | |
+34(0922)-783-692 | +34 922783692 | |
5 3 2 8 2 3 4 6 7 | +420 532 823 467 | |
1 (919) 447-3000 | +1 9194473000 | |
Remarks |
Postal Code | ||
---|---|---|
Description | The Standardization definition for Postal Code standardizes postal codes. | |
Input | Output | |
Examples | -15000 | 15000 |
26000, | 26000 | |
Remarks |
In addition to the definitions listed on this page, the Czech, Czech Republic locale also inherits all definitions for the Czech language and all Global definitions.
Documentation Feedback: yourturn@sas.com
|
Doc ID: QKBCI_CSCZE_defs.html |