Triple
T38480944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heyneke Meyer |
E915672
|
entity |
| Predicate | notableTeamTypeCoached |
P204678
|
FINISHED |
| Object | national team |
—
|
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: national team | Statement: [Heyneke Meyer, notableTeamTypeCoached, national team]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableTeamTypeCoached Context triple: [Heyneke Meyer, notableTeamTypeCoached, national team]
-
A.
notableTeamCoached
Indicates that a person has served as a coach for a team that is considered notable or significant.
-
B.
gamesCoachedWithTeam
Indicates the number of games a coach has led while associated with a specific team.
-
C.
notableCoachAssociationTeam1
Indicates a notable coaching relationship in which the referenced coach is significantly associated with the first team in a given context.
-
D.
notablePlayersCoached
Indicates that a coach has trained or mentored specific players who are considered notable or distinguished in their field.
-
E.
teamCoachedFrom
Indicates that a coaching relationship exists where a coach is responsible for training or managing a team originating from a specific organization, location, or context.
- 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_69f76e8ff5cc8190a88803369183845e |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a1e32108190897356d6a7fed879 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:31 p.m.