Triple
T4079778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Army Sergeants Major Academy |
E87448
|
entity |
| Predicate | trainsForRank |
P14268
|
FINISHED |
| Object | sergeant major |
—
|
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: sergeant major | Statement: [United States Army Sergeants Major Academy, trainsForRank, sergeant major]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainsForRank Context triple: [United States Army Sergeants Major Academy, trainsForRank, sergeant major]
-
A.
trainsForOccupation
chosen
Indicates that an entity undergoes training or preparation aimed at qualifying for or performing a specific occupation.
-
B.
trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
-
C.
notableTrain
Indicates that there is a train or rail service associated with the subject that is considered notable or significant in some way.
-
D.
trainsArtistsFor
Indicates a relationship where one entity provides instruction or guidance to prepare another entity to become or work as an artist.
-
E.
trainConfiguration
Indicates the specific arrangement and composition of train elements (such as locomotives and cars) used together for a particular operation or service.
- 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_69aed9435cf48190ad1da737c962d19d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefc5087b081909d6042bfe8d8a306 |
completed | March 9, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69aef9082c2081908474f082a49bebc8 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:39 p.m.