Triple
T27626785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al Arbour |
E696228
|
entity |
| Predicate | numberOfStanleyCupsWonAsCoach |
P21712
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Al Arbour, numberOfStanleyCupsWonAsCoach, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfStanleyCupsWonAsCoach Context triple: [Al Arbour, numberOfStanleyCupsWonAsCoach, 4]
-
A.
numberOfStanleyCupsAsCoachOrExecutive
Indicates the total count of Stanley Cup championships an individual has won specifically in the roles of coach or executive.
-
B.
totalStanleyCupsAsHeadCoach
chosen
Indicates the total number of Stanley Cup championships an individual has won in the role of head coach.
-
C.
GreyCupsWonAsCoach
Indicates the number of Grey Cup championships a person has won in the role of head coach.
-
D.
CalderCupWonAsCoach
Indicates that the subject served as a coach for a team that won the Calder Cup.
-
E.
championshipWonAsCoach
Indicates that the subject, acting in the role of coach, has won a championship title with the associated team or organization.
- 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_69ef59092c8881908114ad184248cc46 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69fef8c3f2388190b995ec173512945a |
completed | May 9, 2026, 9:05 a.m. |
| PD | Predicate disambiguation | batch_69fef65975608190960b78d27e806d4f |
completed | May 9, 2026, 8:54 a.m. |
Created at: April 27, 2026, 2:18 p.m.