Triple
T30569875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Gable |
E778094
|
entity |
| Predicate | BigTenTeamTitlesAsCoach |
P169852
|
FINISHED |
| Object | 21 |
—
|
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: 21 | Statement: [Dan Gable, BigTenTeamTitlesAsCoach, 21]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: BigTenTeamTitlesAsCoach Context triple: [Dan Gable, BigTenTeamTitlesAsCoach, 21]
-
A.
numberOfTimesAwardedBigTenCoachOfTheYear
Indicates how many times an individual has received the Big Ten Coach of the Year award.
-
B.
collegeTeamCoached
Indicates that a person has served as a coach for a particular college sports team.
-
C.
nationalChampionshipsWonAsCoach
Indicates the number of national championship titles an individual has won specifically in the role of a coach.
-
D.
numberOfPac10CoachOfTheYearAwards
Indicates the number of times an entity has received the Pac-10 Coach of the Year award.
-
E.
GreyCupsWonAsCoach
Indicates the number of Grey Cup championships a person has won in the role of head coach.
- 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_69f2249f8c148190ae7eb3912cde112a |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68911752c8190bc42c92fce473f3c |
completed | May 2, 2026, 11:30 p.m. |
| PD | Predicate disambiguation | batch_69f67e42d6688190b60e91d2c388c555 |
completed | May 2, 2026, 10:44 p.m. |
| PDg | Predicate description generation | batch_69f6827a7b9c8190ab13605aacc81df9 |
completed | May 2, 2026, 11:02 p.m. |
Created at: April 29, 2026, 8:22 p.m.