Triple
T1937445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steve Pikiell |
E41473
|
entity |
| Predicate | typeOfCoach |
P24898
|
FINISHED |
| Object | college head coach |
—
|
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: college head coach | Statement: [Steve Pikiell, typeOfCoach, college head coach]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfCoach Context triple: [Steve Pikiell, typeOfCoach, college head coach]
-
A.
usesCoachType
Indicates that an entity employs or operates a specific type or category of coach (e.g., vehicle or carriage) in its service or context.
-
B.
coachType
chosen
Indicates the specific category or role of a coach associated with an entity (e.g., head coach, assistant coach, position coach).
-
C.
coachOf
Indicates that one entity serves as the coach (trainer or manager) of another entity, typically a person or team.
-
D.
coachingSpecialty
Indicates that a coach focuses on or is specialized in a particular area, topic, or type of coaching.
-
E.
coachesLevel
Indicates the level or tier at which one entity coaches another, such as their rank, division, or proficiency category in a coaching context.
- 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_69a88649b24c819080047f26b6db2ded |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb2c752fc81909baf38ff1cdeb18c |
completed | March 7, 2026, 5:08 a.m. |
| PD | Predicate disambiguation | batch_69abaff07cf88190b4883c5f17f90abd |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.