Triple
T425521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rutgers Scarlet Knights women’s basketball |
E8198
|
entity |
| Predicate | coachTenureStart |
P7106
|
FINISHED |
| Object | C. Vivian Stringer – 1995 |
—
|
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: C. Vivian Stringer – 1995 | Statement: [Rutgers Scarlet Knights women’s basketball, coachTenureStart, C. Vivian Stringer – 1995]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coachTenureStart Context triple: [Rutgers Scarlet Knights women’s basketball, coachTenureStart, C. Vivian Stringer – 1995]
-
A.
headCoachStartYear
chosen
Indicates the year in which an individual began serving as the head coach of a team or organization.
-
B.
headCoachTenure
Indicates the duration or period during which a specific individual serves as the head coach of a team or organization.
-
C.
hiredAsHeadCoachYear
Indicates the year in which an individual was hired to serve as the head coach of a team or organization.
-
D.
managerDebutYear
Indicates the year in which an individual first began their role as a manager.
-
E.
playerCoachChampionshipYears
Indicates the years in which a specific coach led a particular player to win a championship.
- 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eed56ab481909eec289075496260 |
completed | Feb. 28, 2026, 1:34 p.m. |
| PD | Predicate disambiguation | batch_69a2edd6736c81909a6ca549f77b4345 |
completed | Feb. 28, 2026, 1:29 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.