Triple
T7521483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jack Parker |
E177779
|
entity |
| Predicate | totalNCAAChampionshipsAsHeadCoach |
P55955
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Jack Parker, totalNCAAChampionshipsAsHeadCoach, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalNCAAChampionshipsAsHeadCoach Context triple: [Jack Parker, totalNCAAChampionshipsAsHeadCoach, 3]
-
A.
nationalChampionshipsWonAsCoach
chosen
Indicates the number of national championship titles an individual has won specifically in the role of a coach.
-
B.
numberOfNBAChampionshipsAsHeadCoach
Indicates the count of NBA championship titles an individual has won while serving as a head coach.
-
C.
NCAAChampionshipCount
Indicates the number of NCAA championships an entity has won.
-
D.
gamesWonAsHeadCoach
Indicates the number of games that an individual has won while serving in the role of head coach.
-
E.
numberOfTimesAwardedBigTenCoachOfTheYear
Indicates how many times an individual has received the Big Ten Coach of the Year award.
- 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_69c69f29bf3081909a146aec7755f185 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f7c2ad6c8190b822c0a5b80e7829 |
completed | March 27, 2026, 9:33 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d6bb808190bdd04499fd3bceb6 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:46 p.m.