Triple
T34364166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sana |
E881962
|
entity |
| Predicate | trainingCompany |
P2858
|
FINISHED |
| Object | JYP Entertainment |
—
|
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: JYP Entertainment | Statement: [Sana, trainingCompany, JYP Entertainment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainingCompany Context triple: [Sana, trainingCompany, JYP Entertainment]
-
A.
trainingInstitution
chosen
Indicates that one entity serves as the institution or organization where another entity receives training or education.
-
B.
trainingPlatform
Indicates that one entity serves as a platform or environment used to deliver, manage, or conduct training activities for another entity.
-
C.
trainingSystem
Indicates a system or framework used to train, instruct, or develop skills or knowledge in a target entity.
-
D.
trainingIn
Indicates that one entity is undergoing or receiving training within the context, program, or domain specified by another entity.
-
E.
trainingComponent
Indicates that one entity functions as a training-related part, module, or element within a larger training process or system involving another entity.
- 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_69f349be5c9c81908dc726ae1f4c68f2 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f731cc6d1881908f80386ef4d70a09 |
completed | May 3, 2026, 11:30 a.m. |
| PD | Predicate disambiguation | batch_69f7317779e08190bf85777578221a6b |
completed | May 3, 2026, 11:28 a.m. |
Created at: May 1, 2026, 1:58 a.m.