Triple
T15319057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Platoon Leaders Class |
E366238
|
entity |
| Predicate | trainingPeriod |
P118093
|
FINISHED |
| Object | summer training |
—
|
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: summer training | Statement: [Platoon Leaders Class, trainingPeriod, summer training]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainingPeriod Context triple: [Platoon Leaders Class, trainingPeriod, summer training]
-
A.
trainingUnder
Indicates that one entity is receiving instruction, guidance, or mentorship from another, typically in a subordinate or apprentice-like capacity.
-
B.
trainingUse
Indicates that something is used for training purposes, such as preparing, educating, or improving the skills or performance of an entity.
-
C.
trainingVersion
Indicates that one entity is a specific training iteration, release, or configuration derived from or associated with another entity.
-
D.
trainingParadigm
Indicates the specific methodological framework or approach used to train an entity (such as a model, system, or agent).
-
E.
training
Indicates that one entity is teaching, coaching, or otherwise helping another entity acquire or improve a skill, behavior, or capability.
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03dd356b881908f054b64eee6a371 |
completed | April 16, 2026, 1:39 a.m. |
| PD | Predicate disambiguation | batch_69deca9659f48190b8661df223ce5078 |
completed | April 14, 2026, 11:15 p.m. |
| PDg | Predicate description generation | batch_69decf2e413481909d9180a8d78d2c17 |
completed | April 14, 2026, 11:35 p.m. |
Created at: April 10, 2026, 3:16 a.m.