Triple
T23576071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Epic in Miami |
E580259
|
entity |
| Predicate | hasWinningCoach |
P153238
|
FINISHED |
| Object | Don Coryell |
—
|
NE NERFINISHED |
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: Don Coryell | Statement: [The Epic in Miami, hasWinningCoach, Don Coryell]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWinningCoach Context triple: [The Epic in Miami, hasWinningCoach, Don Coryell]
-
A.
headCoachWinningTeam
Indicates that the subject is the head coach of the team that won a particular game, match, or competition.
-
B.
hasLosingTeamCoach
Indicates that a particular game, match, or competition is associated with the coach of the team that lost.
-
C.
championshipWonAsCoach
Indicates that the subject, acting in the role of coach, has won a championship title with the associated team or organization.
-
D.
winningCoachSchool
Indicates that a particular school is the one whose team was coached by the winning coach in a given competition or event.
-
E.
returnedAsHeadCoach
Indicates that an individual resumed a previous role as head coach of a team or organization after a period of absence.
- F. None of above. chosen
Provenance (4 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_69e24601a9108190bc31e83833c980e4 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1afd6608481909a0d293ba8f65b2b |
completed | April 29, 2026, 7:14 a.m. |
| PD | Predicate disambiguation | batch_69f118bcc0b08190b25a8dddfd461a0e |
completed | April 28, 2026, 8:29 p.m. |
| PDg | Predicate description generation | batch_69f12760784c8190aaeff002ef31febe |
completed | April 28, 2026, 9:32 p.m. |
Created at: April 17, 2026, 6:38 p.m.