Centre for Collaboration with Modelling Networks
E535544
The Centre for Collaboration with Modelling Networks is a specialized unit within Norway’s public health system that coordinates and advances the use of mathematical and computational models to inform public health decision-making and policy.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Centre for Collaboration with Modelling Networks canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T5652024 — 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.
Target entity: Centre for Collaboration with Modelling Networks Context triple: [Norwegian Institute of Public Health, hasPart, Centre for Collaboration with Modelling Networks]
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A.
Centre for Modeling and Simulation
The Centre for Modeling and Simulation is an interdisciplinary academic and research unit specializing in computational science, modeling, and simulation across science and engineering domains.
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B.
Blavatnik Interdisciplinary Cyber Research Center
The Blavatnik Interdisciplinary Cyber Research Center is a leading academic hub at Tel Aviv University dedicated to advancing research, policy, and innovation in cybersecurity and related digital domains.
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C.
Robert Bosch Centre for Data Science and Artificial Intelligence
The Robert Bosch Centre for Data Science and Artificial Intelligence is a leading interdisciplinary research hub focused on advancing AI and data science through cutting-edge research, innovation, and industry collaboration.
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D.
Symbiosis Institute of Computer Studies and Research
Symbiosis Institute of Computer Studies and Research is a premier Indian institute offering undergraduate and postgraduate programs in computer science and information technology, known for its industry-oriented curriculum and affiliation with Symbiosis International University.
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E.
Centre for Artificial Intelligence and Data Science
The Centre for Artificial Intelligence and Data Science is a research hub at Nanyang Technological University focused on advancing AI and data science technologies and their real-world applications.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: Centre for Collaboration with Modelling Networks Target entity description: The Centre for Collaboration with Modelling Networks is a specialized unit within Norway’s public health system that coordinates and advances the use of mathematical and computational models to inform public health decision-making and policy.
-
A.
Centre for Modeling and Simulation
The Centre for Modeling and Simulation is an interdisciplinary academic and research unit specializing in computational science, modeling, and simulation across science and engineering domains.
-
B.
Blavatnik Interdisciplinary Cyber Research Center
The Blavatnik Interdisciplinary Cyber Research Center is a leading academic hub at Tel Aviv University dedicated to advancing research, policy, and innovation in cybersecurity and related digital domains.
-
C.
Robert Bosch Centre for Data Science and Artificial Intelligence
The Robert Bosch Centre for Data Science and Artificial Intelligence is a leading interdisciplinary research hub focused on advancing AI and data science through cutting-edge research, innovation, and industry collaboration.
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D.
Symbiosis Institute of Computer Studies and Research
Symbiosis Institute of Computer Studies and Research is a premier Indian institute offering undergraduate and postgraduate programs in computer science and information technology, known for its industry-oriented curriculum and affiliation with Symbiosis International University.
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E.
Centre for Artificial Intelligence and Data Science
The Centre for Artificial Intelligence and Data Science is a research hub at Nanyang Technological University focused on advancing AI and data science technologies and their real-world applications.
- F. None of above. chosen
Statements (35)
| Predicate | Object |
|---|---|
| instanceOf |
government unit
ⓘ
public health research centre ⓘ scientific collaboration centre ⓘ |
| activity |
capacity building in modelling for public health authorities
ⓘ
collaboration with academic and research institutions ⓘ coordination of modelling networks ⓘ development of computational models for public health ⓘ development of mathematical models for public health ⓘ support to policymakers with model-based evidence ⓘ |
| affiliation | Norwegian public health system ⓘ |
| country | Norway ⓘ |
| domain |
health policy analysis
ⓘ
infectious disease modelling ⓘ public health decision support ⓘ |
| field |
computational modelling
ⓘ
epidemiology ⓘ health policy ⓘ health systems research ⓘ mathematical modelling ⓘ public health ⓘ |
| focus |
collaboration between modellers and public health authorities
ⓘ
integration of modelling into routine public health practice ⓘ |
| goal |
to improve evidence-based public health decisions in Norway
ⓘ
to strengthen national modelling infrastructure for public health ⓘ |
| locatedIn | Norway ⓘ |
| purpose |
to advance modelling capacity in public health
ⓘ
to coordinate the use of mathematical and computational models in public health ⓘ to inform public health decision-making ⓘ to inform public health policy ⓘ |
| sector | public sector ⓘ |
| typeOfOrganization | specialized unit within the public health system ⓘ |
| usesMethod |
computational models
ⓘ
mathematical models ⓘ scenario analysis ⓘ simulation modelling ⓘ |
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.
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.
Subject: Centre for Collaboration with Modelling Networks Description of subject: The Centre for Collaboration with Modelling Networks is a specialized unit within Norway’s public health system that coordinates and advances the use of mathematical and computational models to inform public health decision-making and policy.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.