Correa-Milà
E562475
Correa-Milà is an architectural firm known for its role in modernizing and adapting Barcelona’s historic Estadi Olímpic Lluís Companys.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Correa-Milà canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T6002010 — 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: Correa-Milà Context triple: [Estadi Olímpic Lluís Companys, renovationArchitect, Correa-Milà]
-
A.
Correa
Correa is a Spanish-language surname borne by various notable individuals, including politicians, athletes, and artists across the Spanish-speaking world.
-
B.
Oliba Cabreta
Oliba Cabreta was a 10th-century Catalan count who played a key role in consolidating and expanding the power of the counties of Cerdanya and Besalú in the eastern Pyrenees.
-
C.
Echeandía
Echeandía is a small town in central Ecuador known for its agricultural activities and rural Andean setting.
-
D.
Joan Bruna
Joan Bruna is a mathematician and computer scientist known for his foundational work in theoretical deep learning, including convolutional architectures and scattering networks.
-
E.
Miquel
Miquel is a given name, commonly used in Catalan and other languages, that corresponds to the English name Michael.
- 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: Correa-Milà Target entity description: Correa-Milà is an architectural firm known for its role in modernizing and adapting Barcelona’s historic Estadi Olímpic Lluís Companys.
-
A.
Correa
Correa is a Spanish-language surname borne by various notable individuals, including politicians, athletes, and artists across the Spanish-speaking world.
-
B.
Oliba Cabreta
Oliba Cabreta was a 10th-century Catalan count who played a key role in consolidating and expanding the power of the counties of Cerdanya and Besalú in the eastern Pyrenees.
-
C.
Echeandía
Echeandía is a small town in central Ecuador known for its agricultural activities and rural Andean setting.
-
D.
Joan Bruna
Joan Bruna is a mathematician and computer scientist known for his foundational work in theoretical deep learning, including convolutional architectures and scattering networks.
-
E.
Miquel
Miquel is a given name, commonly used in Catalan and other languages, that corresponds to the English name Michael.
- F. None of above. chosen
Statements (16)
| Predicate | Object |
|---|---|
| instanceOf |
architectural firm
ⓘ
architecture studio ⓘ |
| activity |
adapting sports venues
ⓘ
modernizing historic buildings ⓘ |
| associatedWith | Estadi Olímpic Lluís Companys ⓘ |
| city | Barcelona ⓘ |
| country | Spain ⓘ |
| designApproach |
integration of modern elements into historic architecture
ⓘ
modernization of existing stadium infrastructure ⓘ |
| field | architecture ⓘ |
| notableProjectLocation |
Estadi Olímpic Lluís Companys, Barcelona
ⓘ
linked to:
Estadi Olímpic Lluís Companys
|
| notableWork | modernization of Estadi Olímpic Lluís Companys ⓘ |
| regionOfActivity |
Barcelona metropolitan area
ⓘ
linked to:
Metropolitan Area of Barcelona
Catalonia ⓘ |
| specialization |
adaptive reuse of historic structures
ⓘ
sports architecture ⓘ |
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: Correa-Milà Description of subject: Correa-Milà is an architectural firm known for its role in modernizing and adapting Barcelona’s historic Estadi Olímpic Lluís Companys.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.