RSMC Montreal
E221590
RSMC Montreal is a World Meteorological Organization-designated center in Canada that provides specialized meteorological services, particularly for environmental emergencies such as atmospheric transport and dispersion of pollutants.
All labels observed (1)
| Label | Occurrences |
|---|---|
| RSMC Montreal canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T1744618 — 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: RSMC Montreal Context triple: [Regional Specialized Meteorological Centres, hasMember, RSMC Montreal]
-
A.
RSMC Honolulu
RSMC Honolulu is a World Meteorological Organization-designated center responsible for specialized tropical cyclone forecasting and related meteorological services in the Central Pacific region.
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B.
RSMC Exeter
RSMC Exeter is a specialized World Meteorological Organization center based in Exeter, UK, responsible for providing expert meteorological services and guidance, particularly for high-impact weather events.
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C.
RSMC Nadi
RSMC Nadi is a World Meteorological Organization-designated regional center in Fiji responsible for tropical cyclone forecasting and warnings in the South Pacific region.
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D.
RSMC Wellington
RSMC Wellington is a specialized meteorological center operated by New Zealand’s MetService that provides regional forecasting and warning services, particularly for severe weather and tropical cyclones in the South Pacific.
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E.
RSMC Melbourne
RSMC Melbourne is a World Meteorological Organization-designated center in Australia that provides specialized meteorological services, particularly for tropical cyclone and severe weather monitoring and forecasting in its assigned region.
- 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: RSMC Montreal Target entity description: RSMC Montreal is a World Meteorological Organization-designated center in Canada that provides specialized meteorological services, particularly for environmental emergencies such as atmospheric transport and dispersion of pollutants.
-
A.
RSMC Honolulu
RSMC Honolulu is a World Meteorological Organization-designated center responsible for specialized tropical cyclone forecasting and related meteorological services in the Central Pacific region.
-
B.
RSMC Exeter
RSMC Exeter is a specialized World Meteorological Organization center based in Exeter, UK, responsible for providing expert meteorological services and guidance, particularly for high-impact weather events.
-
C.
RSMC Nadi
RSMC Nadi is a World Meteorological Organization-designated regional center in Fiji responsible for tropical cyclone forecasting and warnings in the South Pacific region.
-
D.
RSMC Wellington
RSMC Wellington is a specialized meteorological center operated by New Zealand’s MetService that provides regional forecasting and warning services, particularly for severe weather and tropical cyclones in the South Pacific.
-
E.
RSMC Melbourne
RSMC Melbourne is a World Meteorological Organization-designated center in Australia that provides specialized meteorological services, particularly for tropical cyclone and severe weather monitoring and forecasting in its assigned region.
- F. None of above. chosen
Statements (46)
| Predicate | Object |
|---|---|
| instanceOf |
Regional Specialized Meteorological Centre
ⓘ
meteorological centre ⓘ |
| abbreviation | RSMC Montreal ⓘ |
| affiliatedWith | World Meteorological Organization ⓘ |
| cooperatesWith |
International Atomic Energy Agency
ⓘ
other WMO Regional Specialized Meteorological Centres ⓘ |
| country | Canada ⓘ |
| designatedBy | World Meteorological Organization ⓘ |
| domain |
disaster risk reduction
ⓘ
environmental protection ⓘ meteorology ⓘ |
| focus |
accidental releases from industrial facilities
ⓘ
atmospheric transport of hazardous substances ⓘ long-range transport of air pollutants ⓘ nuclear power plant accident scenarios ⓘ transboundary air pollution events ⓘ |
| hasRole |
atmospheric transport and dispersion modelling
ⓘ
chemical accident emergency support ⓘ environmental emergency response support ⓘ nuclear emergency response support ⓘ pollutant dispersion forecasting ⓘ provision of specialized meteorological services ⓘ radiological emergency support ⓘ |
| language |
English
ⓘ
French ⓘ |
| locatedIn | Montreal ⓘ |
| operatedBy |
Canadian Meteorological Centre
ⓘ
linked to:
Environment and Climate Change Canada
Environment and Climate Change Canada ⓘ |
| partOf |
WMO Environmental Emergency Response programme
ⓘ
WMO network of Regional Specialized Meteorological Centres ⓘ
linked to:
Regional Specialized Meteorological Centres
|
| provides |
meteorological guidance for emergency managers
ⓘ
numerical atmospheric dispersion forecasts ⓘ specialized forecast products for environmental emergencies ⓘ trajectory calculations for pollutant plumes ⓘ |
| serviceArea |
North America
ⓘ
Northern Hemisphere ⓘ global ⓘ |
| supports |
civil protection authorities
ⓘ
international emergency response mechanisms ⓘ national meteorological and hydrological services ⓘ |
| typeOfEmergency |
chemical emergency
ⓘ
environmental emergency ⓘ nuclear emergency ⓘ radiological emergency ⓘ |
| uses |
atmospheric transport and dispersion models
ⓘ
numerical weather prediction models ⓘ |
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: RSMC Montreal Description of subject: RSMC Montreal is a World Meteorological Organization-designated center in Canada that provides specialized meteorological services, particularly for environmental emergencies such as atmospheric transport and dispersion of pollutants.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.