Triple
T4619458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calmecac |
E100941
|
entity |
| Predicate | trainingEmphasized |
P57031
|
FINISHED |
| Object | discipline |
—
|
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: discipline | Statement: [Calmecac, trainingEmphasized, discipline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainingEmphasized Context triple: [Calmecac, trainingEmphasized, discipline]
-
A.
training
Indicates that one entity is teaching, coaching, or otherwise helping another entity acquire or improve a skill, behavior, or capability.
-
B.
trainingUse
Indicates that something is used for training purposes, such as preparing, educating, or improving the skills or performance of an entity.
-
C.
trainingLeadsTo
Indicates that a process of training results in or brings about a particular outcome, state, or effect.
-
D.
trainingComponent
Indicates that one entity functions as a training-related part, module, or element within a larger training process or system involving another entity.
-
E.
trainingGround
Indicates a location or context where entities engage in practice, drills, or preparation activities to develop or improve skills.
- 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_69bd43cf363c819087fd5ab441b4a3f4 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd59e3e6948190925e2cfad20dcc8c |
completed | March 20, 2026, 2:29 p.m. |
| PD | Predicate disambiguation | batch_69bd522fd5c48190ad2bffc0a5bc9061 |
completed | March 20, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69bd556b93cc8190ab817d2817109a0b |
completed | March 20, 2026, 2:10 p.m. |
Created at: March 20, 2026, 1:12 p.m.