Triple
T13805535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Telus Cup |
E331751
|
entity |
| Predicate | sponsor |
P67
|
FINISHED |
| Object | Telus |
E254086
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Telus | Statement: [Telus Cup, sponsor, Telus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Telus Context triple: [Telus Cup, sponsor, Telus]
-
A.
Telus
chosen
Telus is a major Canadian telecommunications company providing wireless, internet, television, and business communication services across Canada.
-
B.
Rogers Communications
Rogers Communications is a major Canadian telecommunications and media company providing wireless, cable, internet, and broadcasting services nationwide.
-
C.
Quebecor (Videotron)
Quebecor (Videotron) is a major Canadian telecommunications and media company best known for providing cable TV, internet, and wireless services, primarily in Quebec.
-
D.
Rogers Wireless
Rogers Wireless is one of Canada’s largest mobile network operators, providing nationwide wireless voice, data, and related telecommunications services.
-
E.
Shaw Communications
Shaw Communications is a Canadian telecommunications company that provides cable television, internet, and phone services, primarily in Western Canada.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de026d98108190acf366a36d97bf92 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b08db39c8190a76637b36b77d643 |
completed | May 3, 2026, 8:31 p.m. |
Created at: April 9, 2026, 10:12 p.m.