Triple
T14953258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dave Shula |
E372850
|
entity |
| Predicate | headCoachRecordNFL |
P14500
|
FINISHED |
| Object | 19–52 |
—
|
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: 19–52 | Statement: [Dave Shula, headCoachRecordNFL, 19–52]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: headCoachRecordNFL Context triple: [Dave Shula, headCoachRecordNFL, 19–52]
-
A.
NFLHeadCoachRecordIncludes
Indicates that a particular NFL head coach’s record includes a specified game, season, statistic, or outcome as part of their official coaching history.
-
B.
overallNFLHeadCoachingRecordRegularSeason
chosen
Indicates the overall win-loss-tie record a coach has accumulated as an NFL head coach during regular-season games.
-
C.
overallNFLHeadCoachingRecordPostseason
Indicates the win-loss-tie record a head coach has accumulated in NFL postseason (playoff) games.
-
D.
coachingRecordNFLWins
Indicates the number of NFL games a coach has won in their coaching career.
-
E.
NFLTeamCoached
Indicates that a person has served as a coach for a specific NFL team.
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6cb336c8190b8a55106fa8fc500 |
completed | April 15, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69de9a588c2c8190b1245a1c406f447c |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:39 a.m.