TOR
E84202
TOR is the standard three-letter abbreviation used to represent the Toronto Maple Leafs in sports standings, statistics, and media.
All labels observed (1)
| Label | Occurrences |
|---|---|
| TOR canonical | 7 |
How this entity was disambiguated
This entity first appeared as the object of triple T706156 — 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: TOR Context triple: [Toronto Maple Leafs, abbreviation, TOR]
-
A.
TER
TER is a network of regional express trains in France that provides local passenger rail services across various regions.
-
B.
Tur
Tur is a foundational 14th-century Jewish legal code by Rabbi Jacob ben Asher that systematically organized halakhic rulings and served as a primary basis for later works like the Shulchan Aruch.
-
C.
TU
TU is the international vehicle registration code assigned to Tunisia.
-
D.
TW
TW is the two-letter ISO 3166 country code assigned to Taiwan (commonly referred to as Chinese Taipei in certain international contexts).
-
E.
TR
TR is the two-letter ISO 3166-1 alpha-2 country code assigned to Turkey for international standardization and referencing.
- 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: TOR Target entity description: TOR is the standard three-letter abbreviation used to represent the Toronto Maple Leafs in sports standings, statistics, and media.
-
A.
TER
TER is a network of regional express trains in France that provides local passenger rail services across various regions.
-
B.
Tur
Tur is a foundational 14th-century Jewish legal code by Rabbi Jacob ben Asher that systematically organized halakhic rulings and served as a primary basis for later works like the Shulchan Aruch.
-
C.
TU
TU is the international vehicle registration code assigned to Tunisia.
-
D.
TW
TW is the two-letter ISO 3166 country code assigned to Taiwan (commonly referred to as Chinese Taipei in certain international contexts).
-
E.
TR
TR is the two-letter ISO 3166-1 alpha-2 country code assigned to Turkey for international standardization and referencing.
- F. None of above. chosen
Statements (48)
| Predicate | Object |
|---|---|
| instanceOf |
sports team abbreviation
ⓘ
three-letter team code ⓘ |
| ambiguityNote | can also be an abbreviation for Toronto in other sports contexts ⓘ |
| associatedWith |
Toronto Maple Leafs logo
ⓘ
Toronto Maple Leafs team colors ⓘ |
| capitalization | uppercase ⓘ |
| codeLength | 3 letters ⓘ |
| codeType | NHL team abbreviation ⓘ |
| context |
North American sports
ⓘ
professional ice hockey ⓘ |
| country | Canada ⓘ |
| displayRole | short form of team name ⓘ |
| league | National Hockey League ⓘ |
| notationRole | team identifier ⓘ |
| represents | Toronto Maple Leafs ⓘ |
| sport | ice hockey ⓘ |
| standardizedBy | National Hockey League ⓘ |
| teamCity | Toronto ⓘ |
| teamName |
Maple Leafs
ⓘ
linked to:
Toronto Maple Leafs
|
| usedIn |
NHL official game reports
ⓘ
NHL schedule listings ⓘ NHL standings ⓘ box scores ⓘ fantasy hockey platforms ⓘ game summaries ⓘ historical NHL records ⓘ league-wide stat leaderboards ⓘ live game trackers ⓘ mobile sports apps ⓘ online box score pages ⓘ online sports tickers ⓘ playoff brackets ⓘ radio and TV broadcast graphics ⓘ score tickers ⓘ social media game updates ⓘ sports analytics reports ⓘ sports betting lines ⓘ sports data APIs ⓘ sports media ⓘ sports news graphics ⓘ sports pages in newspapers ⓘ sports statistics ⓘ statistical databases ⓘ team comparison tables ⓘ team standings tables ⓘ television score bugs ⓘ |
| usedSince | 20th century ⓘ |
| writtenForm | TOR ⓘ |
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: TOR Description of subject: TOR is the standard three-letter abbreviation used to represent the Toronto Maple Leafs in sports standings, statistics, and media.
Referenced by (7)
Full triples — surface form annotated when it differs from this entity's canonical label.