Triple
T23769109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryu Jong-hyun |
E587472
|
entity |
| Predicate | coachedEarlyCareerOf |
P153882
|
FINISHED |
| Object | Yuna Kim |
—
|
NE NERFINISHED |
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: Yuna Kim | Statement: [Ryu Jong-hyun, coachedEarlyCareerOf, Yuna Kim]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coachedEarlyCareerOf Context triple: [Ryu Jong-hyun, coachedEarlyCareerOf, Yuna Kim]
-
A.
hasCoachedFor
Indicates that one entity has served in a coaching role for another entity, such as a team, organization, or individual.
-
B.
coachedAlongside
Indicates that two or more individuals served as coaches at the same time, typically for the same team, organization, or event.
-
C.
coachedFrom
Indicates that one entity served as a coach or trainer for another entity during a specified period or context.
-
D.
coachedAthletesAt
Indicates a relationship where a coach has trained or instructed athletes at a particular organization, team, or location.
-
E.
coachedAtEvent
Indicates that a person served as a coach at a specific event.
- 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_69e2490b8ac48190a6b35f1d5500486b |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1c46507708190b0beba7f2b4d0bca |
completed | April 29, 2026, 8:42 a.m. |
| PD | Predicate disambiguation | batch_69f155f79e34819080f9ddb972b34deb |
completed | April 29, 2026, 12:51 a.m. |
| PDg | Predicate description generation | batch_69f15ed138f88190a8ae555422978908 |
completed | April 29, 2026, 1:28 a.m. |
Created at: April 17, 2026, 7:15 p.m.