Triple
T15003649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jimmy MacElroy |
E377650
|
entity |
| Predicate | trainingRegimen |
P11879
|
FINISHED |
| Object | highly regimented and controlled |
—
|
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: highly regimented and controlled | Statement: [Jimmy MacElroy, trainingRegimen, highly regimented and controlled]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainingRegimen Context triple: [Jimmy MacElroy, trainingRegimen, highly regimented and controlled]
-
A.
trainingBase
Indicates that one entity serves as the training base, site, or facility where another entity receives training or instruction.
-
B.
movementCoach
Indicates a relationship where one entity serves as a coach or instructor guiding another entity’s physical movement or movement-related skills.
-
C.
trainingSystem
chosen
Indicates a system or framework used to train, instruct, or develop skills or knowledge in a target entity.
-
D.
trainingClub
Indicates that one entity serves as a club or organization where the other entity receives training.
-
E.
trainingParadigm
Indicates the specific methodological framework or approach used to train an entity (such as a model, system, or agent).
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7312ae48190bdaf91ecced6657e |
completed | April 15, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69de9a6531a88190acde65199a477350 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:54 a.m.