Mont-Saint-Aignan campus
E1033176
Mont-Saint-Aignan campus is the main university site of the University of Rouen Normandy, located in the town of Mont-Saint-Aignan near Rouen, France.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Mont-Saint-Aignan campus canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T13304378 — 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: Mont-Saint-Aignan campus Context triple: [University of Rouen Normandy, hasCampus, Mont-Saint-Aignan campus]
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A.
Noisy-le-Grand campus
Noisy-le-Grand campus is a primary site of the ESIEE Paris engineering school located in the eastern suburbs of Paris, France.
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B.
Melun campus
Melun campus is a satellite site of Université Paris 2 Panthéon-Assas located in the town of Melun, offering law and related social science programs in a smaller, more localized academic setting.
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C.
Saint-Quentin-en-Yvelines campus
Saint-Quentin-en-Yvelines campus is a major site of the Université de Versailles Saint-Quentin-en-Yvelines, hosting a range of academic, research, and student life facilities in the Yvelines department near Paris.
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D.
Mantes-en-Yvelines campus
Mantes-en-Yvelines campus is a satellite site of the Université de Versailles Saint-Quentin-en-Yvelines that hosts various academic programs and research activities in the Yvelines department of the Île-de-France region.
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E.
Rambouillet campus
Rambouillet campus is a satellite site of the Université de Versailles Saint-Quentin-en-Yvelines located in Rambouillet, France, hosting various higher education programs and student facilities.
- 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: Mont-Saint-Aignan campus Target entity description: Mont-Saint-Aignan campus is the main university site of the University of Rouen Normandy, located in the town of Mont-Saint-Aignan near Rouen, France.
-
A.
Noisy-le-Grand campus
Noisy-le-Grand campus is a primary site of the ESIEE Paris engineering school located in the eastern suburbs of Paris, France.
-
B.
Melun campus
Melun campus is a satellite site of Université Paris 2 Panthéon-Assas located in the town of Melun, offering law and related social science programs in a smaller, more localized academic setting.
-
C.
Saint-Quentin-en-Yvelines campus
Saint-Quentin-en-Yvelines campus is a major site of the Université de Versailles Saint-Quentin-en-Yvelines, hosting a range of academic, research, and student life facilities in the Yvelines department near Paris.
-
D.
Mantes-en-Yvelines campus
Mantes-en-Yvelines campus is a satellite site of the Université de Versailles Saint-Quentin-en-Yvelines that hosts various academic programs and research activities in the Yvelines department of the Île-de-France region.
-
E.
Rambouillet campus
Rambouillet campus is a satellite site of the Université de Versailles Saint-Quentin-en-Yvelines located in Rambouillet, France, hosting various higher education programs and student facilities.
- F. None of above. chosen
Statements (31)
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: Mont-Saint-Aignan campus Description of subject: Mont-Saint-Aignan campus is the main university site of the University of Rouen Normandy, located in the town of Mont-Saint-Aignan near Rouen, France.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.