Triple
T29896108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canada's Top 40 Under 40 |
E759282
|
entity |
| Predicate | numberOfAwardeesPerYear |
P1620
|
FINISHED |
| Object | 40 |
—
|
LITERAL 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: 40 | Statement: [Canada's Top 40 Under 40, numberOfAwardeesPerYear, 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfAwardeesPerYear Context triple: [Canada's Top 40 Under 40, numberOfAwardeesPerYear, 40]
-
A.
numberOfAwardsPerYear
Indicates the number of awards associated with an entity within a given year.
-
B.
typicalNumberOfLaureatesPerYear
chosen
Indicates the usual or average number of laureates associated with a given award or context in a single year.
-
C.
maximumNumberOfLaureatesPerYear
Indicates the highest allowable or observed count of laureates associated with a given year.
-
D.
typicalNumberOfLaureatesPerCycle
Indicates the usual or average number of laureates associated with each award cycle or iteration.
-
E.
numberOfHonoreesPerPeriod
Indicates the count of honorees associated with each defined time period.
- F. None of above.
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_69f2245f1cf88190978c70d1a1d2cb73 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_6a0027e4a59481909417b2531daaf480 |
completed | May 10, 2026, 6:38 a.m. |
| PD | Predicate disambiguation | batch_6a0026a42bc08190ad3322ce625a523a |
completed | May 10, 2026, 6:33 a.m. |
Created at: April 29, 2026, 6:04 p.m.