Triple
T16330718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike Gundy |
E396542
|
entity |
| Predicate | hasCoachedBowlGames |
P42167
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Mike Gundy, hasCoachedBowlGames, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCoachedBowlGames Context triple: [Mike Gundy, hasCoachedBowlGames, true]
-
A.
bowlGamesCoached
chosen
Indicates the number of postseason bowl games in which a coach has served as the head coach for a team.
-
B.
hasCoachedFor
Indicates that one entity has served in a coaching role for another entity, such as a team, organization, or individual.
-
C.
hasCoachedCompetition
Indicates that one entity has served as a coach for another entity in the context of a specific competition or contest.
-
D.
hasCoachedInSuperBowl
Indicates that a person has served as a coach in at least one Super Bowl game.
-
E.
hasCoachedProfessionalSports
Indicates that a person has served in a coaching role for a professional-level sports team or athlete.
- 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_69d87f255b788190a400eba031dd85d8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2c4debef08190a64f13214bfa098f |
completed | April 17, 2026, 11:40 p.m. |
| PD | Predicate disambiguation | batch_69e226eba9b48190af6e80d3d1c2aed3 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:07 a.m.