Triple
T30316457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Machiko Yamada |
E771065
|
entity |
| Predicate | hasNotableTraineeLevel |
P155259
|
FINISHED |
| Object | world champion level athletes |
—
|
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: world champion level athletes | Statement: [Machiko Yamada, hasNotableTraineeLevel, world champion level athletes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableTraineeLevel Context triple: [Machiko Yamada, hasNotableTraineeLevel, world champion level athletes]
-
A.
hasNotableTraineeType
chosen
Indicates that an entity has trainees belonging to a specified notable category or type.
-
B.
hasBeginnerFriendlyTraining
Indicates that an entity provides training or instructional resources suitable for beginners or those with little prior experience.
-
C.
hasTrainingFor
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
-
D.
hasTrainingRole
Indicates that an entity holds or is assigned a specific role within a training or instructional context.
-
E.
hasTrainingTrack
Indicates that an entity is associated with or assigned to a specific training track or program.
- 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_69f22488f224819081b0f3ec41ab975c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a002e71bdc48190b922f2d3b362d259 |
completed | May 10, 2026, 7:06 a.m. |
| PD | Predicate disambiguation | batch_6a002e1a28708190b65f9e657c770bab |
completed | May 10, 2026, 7:04 a.m. |
Created at: April 29, 2026, 7:51 p.m.