canton of Tremblay-en-France
E336048
The canton of Tremblay-en-France is an administrative division in the Seine-Saint-Denis department of the Île-de-France region in northern France, centered on the commune of Tremblay-en-France and its surrounding area.
All labels observed (2)
| Label | Occurrences |
|---|---|
| canton of Tremblay-en-France canonical | 2 |
| canton de Tremblay-en-France | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T3141379 — 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: canton of Tremblay-en-France Context triple: [Tremblay-en-France, partOf, canton of Tremblay-en-France]
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A.
canton of Vauréal
The canton of Vauréal is an administrative division in the Val-d'Oise department of northern France that includes the commune of Vétheuil among its constituent municipalities.
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B.
canton of La Courneuve
The canton of La Courneuve is an administrative division in the Seine-Saint-Denis department of the Île-de-France region in northern France, encompassing several suburban communes northeast of Paris.
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C.
canton of Sarcelles
The canton of Sarcelles is an administrative division in the Val-d'Oise department in the Île-de-France region of northern France, centered on the suburban town of Sarcelles near Paris.
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D.
canton of Orly
The canton of Orly is an administrative division in the Val-de-Marne department in the Île-de-France region of northern France, centered around the suburban town of Orly near Paris.
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E.
Seine-Saint-Denis
Seine-Saint-Denis is a densely populated suburban department northeast of Paris, known for its cultural diversity, working-class communities, and significant role in the metropolitan area’s social and economic life.
- 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: canton of Tremblay-en-France Target entity description: The canton of Tremblay-en-France is an administrative division in the Seine-Saint-Denis department of the Île-de-France region in northern France, centered on the commune of Tremblay-en-France and its surrounding area.
-
A.
canton of Vauréal
The canton of Vauréal is an administrative division in the Val-d'Oise department of northern France that includes the commune of Vétheuil among its constituent municipalities.
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B.
canton of La Courneuve
The canton of La Courneuve is an administrative division in the Seine-Saint-Denis department of the Île-de-France region in northern France, encompassing several suburban communes northeast of Paris.
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C.
canton of Sarcelles
The canton of Sarcelles is an administrative division in the Val-d'Oise department in the Île-de-France region of northern France, centered on the suburban town of Sarcelles near Paris.
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D.
canton of Orly
The canton of Orly is an administrative division in the Val-de-Marne department in the Île-de-France region of northern France, centered around the suburban town of Orly near Paris.
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E.
Seine-Saint-Denis
Seine-Saint-Denis is a densely populated suburban department northeast of Paris, known for its cultural diversity, working-class communities, and significant role in the metropolitan area’s social and economic life.
- F. None of above. chosen
Statements (25)
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: canton of Tremblay-en-France Description of subject: The canton of Tremblay-en-France is an administrative division in the Seine-Saint-Denis department of the Île-de-France region in northern France, centered on the commune of Tremblay-en-France and its surrounding area.
Referenced by (3)
Full triples — surface form annotated when it differs from this entity's canonical label.
canton of Tremblay-en-France
→
hasNameInLanguage
→
canton of Tremblay-en-France
self-linksurface differs
ⓘ
this entity surface form:
canton de Tremblay-en-France