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Portugal has 18 districts which might be considered PROV but they do not explicitly come into play in the addresses. For Navteq data we can extract all the localities which would get tagged as CITY, and then potentially IGNORE the sub-localities.
The issue is not about recognizing them but how to categorize them when we pass them to the geocoder. We currently only CITY, PROV, NATION. We could stuff the CITY (aka: locality) into PROV and then put the sub-locality words into CITY.
Getting more addresses for Portugal and comparing them with real street data will probably make more sense of this.
## Home delivery (large towns):
MANUEL GASPAR addressee
LG DR ANTÓNIO VIANA 1 2 DTO street + premises, floor, side
1250–096 LISBOA postcode + locality
PORTUGAL country
## with sub-locality:
MARIA SILVA ANDRADE addressee
R PRINCIPAL VV ANDRADE street + premises
QUINTA DA PROVENÇA sub-locality level 2
CASAIS NOVOS sub-locality
2580-347 ALENQUER postcode + locality
PORTUGAL country
## Home delivery (rural region):
DR. NUNO FIGUEIREDO addressee
R. LEAL DA CAMARA 31 RL ESQ street + premises, floor, side
ALGUEIRÃO sub-locality
2725–079 MEM MARTINS postcode + locality
PORTUGAL country
## PO Box delivery:
PATRICIA MARTINS addressee
APARTADO 42024 PO Box
EC –D. LUÍS post office
1201–950 LISBOA postcode + locality
PORTUGAL country
## Delivery to private letter boxes:
ENG. MANUEL SOUSA addressee
RUA DAS DESCOBERTAS street
CCI 8318 PO Box
PENTEADO sub-locality
2860–571 MOITA postcode + locality
PORTUGAL country
The current grammar handles these by putting them into the extra field:
Here are some sample addresses from http://www.upu.int/fileadmin/documentsFiles/activities/addressingUnit/prtEn.pdf
The issue is how to handle sub-locality level 2 and sub-locality and locality.
Portugal has 18 districts which might be considered PROV but they do not explicitly come into play in the addresses. For Navteq data we can extract all the localities which would get tagged as CITY, and then potentially IGNORE the sub-localities.
The issue is not about recognizing them but how to categorize them when we pass them to the geocoder. We currently only CITY, PROV, NATION. We could stuff the CITY (aka: locality) into PROV and then put the sub-locality words into CITY.
Getting more addresses for Portugal and comparing them with real street data will probably make more sense of this.
The current grammar handles these by putting them into the extra field:
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