Triple
T33456211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Clair |
E856781
|
entity |
| Predicate | numberOfGreyCupsWonAsCoach |
P155717
|
FINISHED |
| Object | multiple |
—
|
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: multiple | Statement: [Frank Clair, numberOfGreyCupsWonAsCoach, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGreyCupsWonAsCoach Context triple: [Frank Clair, numberOfGreyCupsWonAsCoach, multiple]
-
A.
GreyCupsWonAsCoach
chosen
Indicates the number of Grey Cup championships a person has won in the role of head coach.
-
B.
numberOfStanleyCupsAsCoachOrExecutive
Indicates the total count of Stanley Cup championships an individual has won specifically in the roles of coach or executive.
-
C.
numberOfSuperBowlsWonAsHeadCoach
Indicates the total count of Super Bowl championships an individual has won while serving in the role of head coach.
-
D.
numberOfWorldSeriesTitlesAsCoach
Indicates the number of World Series championship titles an individual has won specifically in the role of a coach.
-
E.
totalStanleyCupsAsHeadCoach
Indicates the total number of Stanley Cup championships an individual has won in the role of head coach.
- 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_69f3497281a08190b4705de0b5f26ba7 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a031c6c728c81909c1d010048df71c3 |
completed | May 12, 2026, 12:26 p.m. |
| PD | Predicate disambiguation | batch_6a031bfc3b74819098c551096b1fcf00 |
completed | May 12, 2026, 12:24 p.m. |
Created at: May 1, 2026, 1:37 a.m.