Triple
T25476920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dick Reynolds |
E638457
|
entity |
| Predicate | coachingYears |
P15414
|
FINISHED |
| Object | 1939–1960 |
—
|
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: 1939–1960 | Statement: [Dick Reynolds, coachingYears, 1939–1960]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coachingYears Context triple: [Dick Reynolds, coachingYears, 1939–1960]
-
A.
yearsActiveAsCoach
chosen
Indicates the span of time, typically in years, during which an individual has served in a coaching role.
-
B.
hasCoachedFor
Indicates that one entity has served in a coaching role for another entity, such as a team, organization, or individual.
-
C.
coachTenureIncludes
Indicates that a coach’s period of service or employment with a team or organization covers or includes a specified time span or event.
-
D.
coachingEra
Indicates the time period during which a particular coach is in charge of a team or individual.
-
E.
activeYearsInCareer
Indicates the span of time during which an entity was actively engaged in a particular career or professional field.
- 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_69e75db9b964819096802dcf502e577e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f772a0248190a52aef4495a5b0a3 |
completed | May 2, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69f480789be08190ab252a6de3797200 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 2:26 p.m.