Triple
T35115066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christopher d'Amboise |
E1013409
|
entity |
| Predicate | hasProfessionalTrainingIn |
—
|
GENERATED |
| Object | classical ballet |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProfessionalTrainingIn Context triple: [Christopher d'Amboise, hasProfessionalTrainingIn, classical ballet]
-
A.
hasHandsOnTraining
Indicates that an entity has received practical, experiential instruction or practice in performing a specific task or activity.
-
B.
trainedAs
Indicates that one entity has received education or instruction to perform the role, profession, or function represented by another entity.
-
C.
receivedTrainingIn
chosen
Indicates that one entity has undergone or been provided with training or instruction in a particular field, skill, or subject associated with another entity.
-
D.
hasTrainingFor
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
-
E.
hasTrainingRole
Indicates that an entity holds or is assigned a specific role within a training or instructional context.
- F. None of above.
Provenance (1 batch)
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_69f76dd659d08190bcdc00d37caafb62 |
completed | May 3, 2026, 3:46 p.m. |
Created at: May 3, 2026, 4:01 p.m.