Les Lilas, Seine-Saint-Denis, France
E1033915
Les Lilas is a small suburban commune just northeast of Paris in the Seine-Saint-Denis department of France, known for its dense urban character and proximity to the capital.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Les Lilas, Seine-Saint-Denis, France canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T13277206 — 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: Les Lilas, Seine-Saint-Denis, France Context triple: [Jean Yanne, placeOfBirth, Les Lilas, Seine-Saint-Denis, France]
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A.
Levallois-Perret, France
Levallois-Perret, France is a densely populated suburban commune just northwest of central Paris, known for its residential neighborhoods and as a base for numerous corporate headquarters.
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B.
Clichy-sous-Bois, France
Clichy-sous-Bois is a northeastern suburb of Paris in the Île-de-France region, known for its diverse population and significant role in contemporary French social and urban history.
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C.
Fontenay-aux-Roses, France
Fontenay-aux-Roses is a suburban commune in the southern outskirts of Paris, known for its residential character and proximity to major academic and research institutions.
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D.
Clichy, Hauts-de-Seine, France
Clichy, Hauts-de-Seine, France is a suburban commune just northwest of central Paris known for hosting major corporate offices and being part of the densely populated inner ring of the Paris metropolitan area.
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E.
Arcueil, Val-de-Marne, France
Arcueil is a suburban commune in the Val-de-Marne department just south of Paris, noted in part for having been the longtime home of composer Erik Satie.
- 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: Les Lilas, Seine-Saint-Denis, France Target entity description: Les Lilas is a small suburban commune just northeast of Paris in the Seine-Saint-Denis department of France, known for its dense urban character and proximity to the capital.
-
A.
Levallois-Perret, France
Levallois-Perret, France is a densely populated suburban commune just northwest of central Paris, known for its residential neighborhoods and as a base for numerous corporate headquarters.
-
B.
Clichy-sous-Bois, France
Clichy-sous-Bois is a northeastern suburb of Paris in the Île-de-France region, known for its diverse population and significant role in contemporary French social and urban history.
-
C.
Fontenay-aux-Roses, France
Fontenay-aux-Roses is a suburban commune in the southern outskirts of Paris, known for its residential character and proximity to major academic and research institutions.
-
D.
Clichy, Hauts-de-Seine, France
Clichy, Hauts-de-Seine, France is a suburban commune just northwest of central Paris known for hosting major corporate offices and being part of the densely populated inner ring of the Paris metropolitan area.
-
E.
Arcueil, Val-de-Marne, France
Arcueil is a suburban commune in the Val-de-Marne department just south of Paris, noted in part for having been the longtime home of composer Erik Satie.
- F. None of above. chosen
Statements (47)
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: Les Lilas, Seine-Saint-Denis, France Description of subject: Les Lilas is a small suburban commune just northeast of Paris in the Seine-Saint-Denis department of France, known for its dense urban character and proximity to the capital.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.