Triple
T37538800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Exodar |
E933274
|
entity |
| Predicate | hasClassTrainersFor |
P195988
|
FINISHED |
| Object | paladin |
—
|
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: paladin | Statement: [Exodar, hasClassTrainersFor, paladin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClassTrainersFor Context triple: [Exodar, hasClassTrainersFor, paladin]
-
A.
hasTrainingFor
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
-
B.
hasOnScreenTrainer
Indicates that an entity has a trainer or instructor who appears on screen (e.g., in a video or broadcast) providing guidance or instruction.
-
C.
hasTrainingBaseIn
Indicates that an entity maintains or operates a training base located in a specified place.
-
D.
hasTrainingRole
Indicates that an entity holds or is assigned a specific role within a training or instructional context.
-
E.
hasTrainingType
Indicates that an entity is associated with or characterized by a specific type or category of training.
- 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_69f76ec999288190ae26ec7b6aea7046 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fdfbafe32081909c62653ff4fc155c |
completed | May 8, 2026, 3:05 p.m. |
| PD | Predicate disambiguation | batch_69fdf64db4a881908f8250e24ae3cefb |
completed | May 8, 2026, 2:42 p.m. |
| PDg | Predicate description generation | batch_69fdfbae00e481908a2e4558b9dee07e |
completed | May 8, 2026, 3:05 p.m. |
Created at: May 3, 2026, 4:17 p.m.