Triple
T33633109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MCPO |
E861618
|
entity |
| Predicate | hasEquivalentRankInUSArmy |
P108197
|
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: [MCPO, hasEquivalentRankInUSArmy, Sergeant Major]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEquivalentRankInUSArmy Context triple: [MCPO, hasEquivalentRankInUSArmy, Sergeant Major]
-
A.
equivalentRankInArmy
Indicates that two entities hold military positions considered to be of the same rank or level within their respective armies.
-
B.
correspondingRankInUSArmy
chosen
Indicates that one military rank is the equivalent or closest matching rank within the hierarchy of the United States Army.
-
C.
equivalentRankInUSAF
Indicates that two military ranks are considered equivalent in status or grade within the United States Air Force.
-
D.
equivalentAirForceRank
Indicates that two military positions or titles correspond to the same rank level within different air forces.
-
E.
equivalentRankInBritishArmy
Indicates that two military positions are considered to have the same rank level within the structure of the British Army.
- 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_69f34981c54c81909b33c3fa2208a52d |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fb19063c81909466b329655c8583 |
completed | May 3, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f6f96badb08190994442c2aba840b1 |
completed | May 3, 2026, 7:29 a.m. |
Created at: May 1, 2026, 1:41 a.m.