RU-SPE
E769183
RU-SPE is the regional code for Saint Petersburg, a federal city and major cultural and economic center in northwestern Russia.
All labels observed (1)
| Label | Occurrences |
|---|---|
| RU-SPE canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T8974087 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RU-SPE Context triple: [Liteyny Municipal Okrug, hasRegionalCode, RU-SPE]
-
A.
Rus
Rus was a medieval East Slavic cultural and political realm that laid the foundations for the modern nations of Russia, Ukraine, and Belarus.
-
B.
RU
RU is the common abbreviation for Rutgers University, a major public research institution in New Jersey.
-
C.
RU
RU is the historic vehicle registration code that was used for the English county of Rutland.
-
D.
RU
RU is the common abbreviation for Radboud University Nijmegen, a major research university located in Nijmegen, the Netherlands.
-
E.
RU
RU is the commonly used abbreviation for the University of Rajshahi, a major public university in Bangladesh.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: RU-SPE Target entity description: RU-SPE is the regional code for Saint Petersburg, a federal city and major cultural and economic center in northwestern Russia.
-
A.
Rus
Rus was a medieval East Slavic cultural and political realm that laid the foundations for the modern nations of Russia, Ukraine, and Belarus.
-
B.
RU
RU is the common abbreviation for Rutgers University, a major public research institution in New Jersey.
-
C.
RU
RU is the historic vehicle registration code that was used for the English county of Rutland.
-
D.
RU
RU is the two-letter ISO 3166 country code for the Russian Federation.
-
E.
RU
RU is the common abbreviation for Radboud University Nijmegen, a major research university located in Nijmegen, the Netherlands.
- F. None of above. chosen
Statements (29)
| Predicate | Object |
|---|---|
| instanceOf |
ISO 3166-2:RU region code
ⓘ
regional code ⓘ |
| appliesTo | territory of Saint Petersburg ⓘ |
| assignedBy | International Organization for Standardization ⓘ |
| classificationLevel | first-level administrative subdivision of Russia ⓘ |
| codeElementType | alphanumeric ⓘ |
| codePart |
RU
ⓘ
SPE ⓘ |
| country | Russia ⓘ |
| countryCode | RU ⓘ |
| geographicalLocation |
northwestern Russia
ⓘ
linked to:
Northwest Russia
|
| governingJurisdiction |
Russian Federation
ⓘ
linked to:
Russia
|
| hasAlternativeRepresentation | RU-SPE (with hyphen as per ISO 3166-2 formatting) ⓘ |
| languageOfCodeElements | Latin alphabet ⓘ |
| notationFormat | two-part code separated by a hyphen ⓘ |
| partOfStandard | ISO 3166-2:RU ⓘ |
| regionName |
Saint Petersburg
ⓘ
linked to:
Saint Petersburg Federal City
|
| regionStatus | federal city ⓘ |
| relatedTo | ISO 3166-1 alpha-2 code RU ⓘ |
| represents |
Saint Petersburg
ⓘ
linked to:
Saint Petersburg Federal City
|
| representsAdministrativeUnitType | federal city of Russia ⓘ |
| standard |
ISO 3166-2
ⓘ
linked to:
ISO 3166
|
| subdivisionCategory |
city
ⓘ
federal city ⓘ |
| usedFor | identifying the federal city of Saint Petersburg within Russia ⓘ |
| usedIn |
administrative records
ⓘ
databases ⓘ geographic information systems ⓘ statistical reporting ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: RU-SPE Description of subject: RU-SPE is the regional code for Saint Petersburg, a federal city and major cultural and economic center in northwestern Russia.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.