Regional Data-processing Centres
E37070
Regional Data-processing Centres are specialized facilities within the Global Data-processing and Forecasting System that collect, process, and analyze regional meteorological and related data to support weather forecasting and climate services.
All labels observed (3)
| Label | Occurrences |
|---|---|
| Regional Data-processing Centres canonical | 2 |
| Global Producing Centres | 1 |
| National Data-processing Centres | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T283565 — 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: Regional Data-processing Centres Context triple: [Global Data-processing and Forecasting System, hasComponent, Regional Data-processing Centres]
-
A.
Center for Information Technology
The Center for Information Technology is the National Institutes of Health’s central organization responsible for providing advanced computing, networking, and information technology services to support biomedical research and administration.
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B.
Norsk Data NORD-10
Norsk Data NORD-10 was a 16-bit minicomputer series from the Norwegian company Norsk Data, widely used in the 1970s and 1980s for scientific, technical, and commercial applications.
-
C.
Defense Data Network
The Defense Data Network was a U.S. Department of Defense global computer network that succeeded ARPANET and supported secure military and government communications.
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D.
Statistical Research Center
The Statistical Research Center is a unit of the American Institute of Physics that conducts and disseminates data-driven studies on education, employment, and demographics in the physical sciences community.
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E.
Enterprise Center
Enterprise Center is a major indoor arena in downtown St. Louis, Missouri, best known as the home of the NHL’s St. Louis Blues and a venue for large concerts and events.
- 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: Regional Data-processing Centres Target entity description: Regional Data-processing Centres are specialized facilities within the Global Data-processing and Forecasting System that collect, process, and analyze regional meteorological and related data to support weather forecasting and climate services.
-
A.
Center for Information Technology
The Center for Information Technology is the National Institutes of Health’s central organization responsible for providing advanced computing, networking, and information technology services to support biomedical research and administration.
-
B.
Norsk Data NORD-10
Norsk Data NORD-10 was a 16-bit minicomputer series from the Norwegian company Norsk Data, widely used in the 1970s and 1980s for scientific, technical, and commercial applications.
-
C.
Defense Data Network
The Defense Data Network was a U.S. Department of Defense global computer network that succeeded ARPANET and supported secure military and government communications.
-
D.
Statistical Research Center
The Statistical Research Center is a unit of the American Institute of Physics that conducts and disseminates data-driven studies on education, employment, and demographics in the physical sciences community.
-
E.
Enterprise Center
Enterprise Center is a major indoor arena in downtown St. Louis, Missouri, best known as the home of the NHL’s St. Louis Blues and a venue for large concerts and events.
- F. None of above. chosen
Statements (47)
| Predicate | Object |
|---|---|
| instanceOf |
component of Global Data-processing and Forecasting System
ⓘ
meteorological data centre ⓘ |
| beneficiary |
agricultural meteorology users in the region
ⓘ
aviation meteorology users in the region ⓘ civil protection authorities in the region ⓘ marine meteorology users in the region ⓘ |
| contributesTo |
multi-hazard early warning systems
ⓘ
regional climate outlooks ⓘ |
| dependsOn |
Global Telecommunication System
ⓘ
surface form:
Global Telecommunication System for data exchange
|
| domain |
climate monitoring
ⓘ
meteorology ⓘ operational weather forecasting ⓘ |
| geographicalScope | specific WMO regions or subregions ⓘ |
| goal |
improve accuracy of regional weather forecasts
ⓘ
support climate services at regional scale ⓘ support early warning systems ⓘ |
| hasFunction |
analysis of regional meteorological data
ⓘ
collection of regional meteorological data ⓘ processing of regional meteorological data ⓘ support of climate services ⓘ support of weather forecasting services ⓘ |
| operatedBy | National Meteorological and Hydrological Services ⓘ |
| partOf | Global Data-processing and Forecasting System ⓘ |
| performs |
archiving of regional meteorological datasets
ⓘ
distribution of regional forecast products ⓘ generation of tailored regional climate information ⓘ quality control of regional meteorological data ⓘ |
| providesServiceTo |
National Meteorological and Hydrological Services in the region
ⓘ
disaster risk reduction agencies ⓘ regional climate centres ⓘ |
| relatedTo |
Global Data-processing Centres
ⓘ
Regional Specialized Meteorological Centres ⓘ World Meteorological Organization ⓘ World Weather Watch ⓘ |
| scale | regional ⓘ |
| supportsProcess |
data assimilation for regional models
ⓘ
generation of regional forecast products ⓘ regional numerical weather prediction ⓘ verification of regional forecasts ⓘ |
| technology |
high-performance computing systems
ⓘ
specialized meteorological data-processing software ⓘ |
| usesDataType |
in-situ surface observations
ⓘ
numerical weather prediction output ⓘ observational meteorological data ⓘ radar meteorological data ⓘ satellite meteorological data ⓘ upper-air observations ⓘ |
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: Regional Data-processing Centres Description of subject: Regional Data-processing Centres are specialized facilities within the Global Data-processing and Forecasting System that collect, process, and analyze regional meteorological and related data to support weather forecasting and climate services.
Referenced by (4)
Full triples — surface form annotated when it differs from this entity's canonical label.
this entity surface form:
Global Producing Centres
this entity surface form:
National Data-processing Centres