Triple
T38591112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jedi Consular |
E932454
|
entity |
| Predicate | trainerOrganization |
P2858
|
FINISHED |
| Object | Jedi Order |
—
|
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: Jedi Order | Statement: [Jedi Consular, trainerOrganization, Jedi Order]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainerOrganization Context triple: [Jedi Consular, trainerOrganization, Jedi Order]
-
A.
trainerAssociation
Indicates a relationship where one entity serves as a trainer, coach, or instructor for another entity.
-
B.
trainingClub
Indicates that one entity serves as a club or organization where the other entity receives training.
-
C.
trainer
Indicates a relationship where one entity teaches, coaches, or prepares another entity to develop skills, knowledge, or performance in a particular domain.
-
D.
coachSchool
Indicates that a person serves as a coach for a particular school or educational institution.
-
E.
trainingInstitution
chosen
Indicates that one entity serves as the institution or organization where another entity receives training or education.
- 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_69f76ec654d48190b421111cf26e54d9 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:32 p.m.