Triple
T15599731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NHL Three Stars of the Week |
E374999
|
entity |
| Predicate | numberOfHonoreesPerPeriod |
P119394
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [NHL Three Stars of the Week, numberOfHonoreesPerPeriod, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfHonoreesPerPeriod Context triple: [NHL Three Stars of the Week, numberOfHonoreesPerPeriod, 3]
-
A.
typicalNumberOfLaureatesPerCycle
Indicates the usual or average number of laureates associated with each award cycle or iteration.
-
B.
maximumNumberOfLaureatesPerYear
Indicates the highest allowable or observed count of laureates associated with a given year.
-
C.
typicalNumberOfLaureatesPerYear
Indicates the usual or average number of laureates associated with a given award or context in a single year.
-
D.
numberOfAwardsPerYear
Indicates the number of awards associated with an entity within a given year.
-
E.
hasNumberOfInductees
Indicates the specific count of inductees associated with a given entity or context.
- F. None of above. chosen
Provenance (4 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_69d85cce25008190b13b52745fbd719b |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e621fc4819097e8e85e7ddfdc6c |
completed | April 16, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69deda844af081909e658ebc9d9b403d |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f05f708190850f1d8782e132b0 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:12 a.m.