Triple
T35881727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clark Savage Sr. |
E1037525
|
entity |
| Predicate | trainingMethodsIncluded |
P16019
|
FINISHED |
| Object | rigorous physical conditioning |
—
|
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: rigorous physical conditioning | Statement: [Clark Savage Sr., trainingMethodsIncluded, rigorous physical conditioning]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainingMethodsIncluded Context triple: [Clark Savage Sr., trainingMethodsIncluded, rigorous physical conditioning]
-
A.
trainingMethod
chosen
Indicates the specific approach, technique, or procedure used to train an entity (such as a person, model, or system).
-
B.
trainingModality
Indicates the method or format through which training or instruction is delivered or conducted.
-
C.
trainingFormat
Indicates the specific method or medium through which training is delivered or conducted.
-
D.
providesTrainingFor
Indicates that one entity delivers or conducts training activities intended to develop the skills or knowledge of another entity.
-
E.
trainingIn
Indicates that one entity is undergoing or receiving training within the context, program, or domain specified by another entity.
- 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_69f76e1f4d748190bb55594d8441d70e |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7b5ccbda481908fe1945c35e36ce8 |
completed | May 3, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c06f5881908f0b98cad6796478 |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 3, 2026, 4:06 p.m.