Triple
T15318895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Infantry Officer Course |
E366234
|
entity |
| Predicate | usesTrainingEnvironment |
P69125
|
FINISHED |
| Object | field training areas |
—
|
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: field training areas | Statement: [Infantry Officer Course, usesTrainingEnvironment, field training areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTrainingEnvironment Context triple: [Infantry Officer Course, usesTrainingEnvironment, field training areas]
-
A.
hasTrainingEnvironment
chosen
Indicates that an entity is associated with, or operates within, a specific environment or setting used for training or practice.
-
B.
usesTrainingStrategy
Indicates that one entity applies or follows a particular training strategy in carrying out its learning or optimization process.
-
C.
trainingUse
Indicates that something is used for training purposes, such as preparing, educating, or improving the skills or performance of an entity.
-
D.
hasTrained
Indicates that one entity has provided training or instruction to another entity.
-
E.
trainingUnder
Indicates that one entity is receiving instruction, guidance, or mentorship from another, typically in a subordinate or apprentice-like capacity.
- 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_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. |
Created at: April 10, 2026, 3:16 a.m.