Triple
T6530881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Army Basic Combat Training installations |
E152226
|
entity |
| Predicate | train |
P788
|
FINISHED |
| Object | Army enlisted recruits |
—
|
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: Army enlisted recruits | Statement: [Army Basic Combat Training installations, train, Army enlisted recruits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: train Context triple: [Army Basic Combat Training installations, train, Army enlisted recruits]
-
A.
trains
chosen
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
-
B.
trainTypeUsed
Indicates that a specific type or category of train is employed or operated in a given context or service.
-
C.
railroad
Indicates that one entity constructs, operates, or provides railroad or train transportation services for another entity or area.
-
D.
trainsOn
Indicates that one entity receives training, instruction, or practice using or based on another entity (such as a resource, dataset, tool, or subject).
-
E.
trainOperation
Indicates that an entity is engaged in operating, running, or managing the movement and service of a train.
- 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_69c688048ec8819093a47f7d332e12ec |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6adac53b0819097fece48a75cc48f |
completed | March 27, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69c68abd9c7c819099e4fe8097cd1b28 |
completed | March 27, 2026, 1:48 p.m. |
Created at: March 27, 2026, 1:46 p.m.