Université du Québec à Montréal
E19016
Université du Québec à Montréal is a major French-language public university known for its urban campus, research activity, and strong presence in the cultural and academic life of Montreal.
All labels observed (5)
| Label | Occurrences |
|---|---|
| Université du Québec à Montréal canonical | 43 |
| UQAM | 2 |
| Montreal North campus | 1 |
| UQAM (Université du Québec à Montréal) | 1 |
| Université du Québec à Montréal administration | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T128744 — 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: Université du Québec à Montréal Context triple: [Montreal, hasUniversity, Université du Québec à Montréal]
-
A.
Université de Montréal
Université de Montréal is a major French-language public research university in Montreal, Canada, renowned for its contributions to fields such as artificial intelligence and deep learning.
-
B.
McGill University
McGill University is a leading public research university in Montreal, Canada, renowned for its strong academic programs, global reputation, and membership in major research-intensive university associations.
-
C.
Concordia University
Concordia University is a major public research university in Montreal, Canada, known for its diverse student body and strong programs in arts, engineering, business, and social sciences.
-
D.
University of Toronto
The University of Toronto is a leading Canadian public research university renowned globally for its academic excellence, extensive research output, and influential alumni.
-
E.
York University
York University is a major public research university in Toronto, Canada, known for its diverse academic programs and large student population.
- 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: Université du Québec à Montréal Target entity description: Université du Québec à Montréal is a major French-language public university known for its urban campus, research activity, and strong presence in the cultural and academic life of Montreal.
-
A.
Université de Montréal
Université de Montréal is a major French-language public research university in Montreal, Canada, renowned for its contributions to fields such as artificial intelligence and deep learning.
-
B.
McGill University
McGill University is a leading public research university in Montreal, Canada, renowned for its strong academic programs, global reputation, and membership in major research-intensive university associations.
-
C.
Concordia University
Concordia University is a major public research university in Montreal, Canada, known for its diverse student body and strong programs in arts, engineering, business, and social sciences.
-
D.
University of Toronto
The University of Toronto is a leading Canadian public research university renowned globally for its academic excellence, extensive research output, and influential alumni.
-
E.
York University
York University is a major public research university in Toronto, Canada, known for its diverse academic programs and large student population.
- F. None of above. chosen
Statements (49)
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: Université du Québec à Montréal Description of subject: Université du Québec à Montréal is a major French-language public university known for its urban campus, research activity, and strong presence in the cultural and academic life of Montreal.
Referenced by (48)
Full triples — surface form annotated when it differs from this entity's canonical label.
Université du Québec à Montréal
→
shortName
→
Université du Québec à Montréal
self-linksurface differs
ⓘ
this entity surface form:
UQAM
Université du Québec à Montréal
→
hasCampus
→
Université du Québec à Montréal
self-linksurface differs
ⓘ
this entity surface form:
Montreal North campus
Université du Québec à Montréal
→
abbreviation
→
Université du Québec à Montréal
self-linksurface differs
ⓘ
this entity surface form:
UQAM
subject surface form:
Université du Québec
subject surface form:
Faculty of Communication (UQAM)
subject surface form:
Faculty of Communication (UQAM)
this entity surface form:
Université du Québec à Montréal administration
subject surface form:
Faculty of Communication (UQAM)
subject surface form:
Faculty of Arts (Université du Québec à Montréal)
subject surface form:
Faculty of Arts (Université du Québec à Montréal)
subject surface form:
Faculty of Education (UQAM)
subject surface form:
Faculty of Science (Université du Québec à Montréal)
subject surface form:
Faculty of Social Sciences (Université du Québec à Montréal)
subject surface form:
Faculty of Social Sciences (Université du Québec à Montréal)
this entity surface form:
UQAM (Université du Québec à Montréal)