Triple
T1239741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Army professional military education system |
E26630
|
entity |
| Predicate | usesModality |
P25869
|
FINISHED |
| Object | resident instruction |
—
|
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: resident instruction | Statement: [Army professional military education system, usesModality, resident instruction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesModality Context triple: [Army professional military education system, usesModality, resident instruction]
-
A.
usesModulation
Indicates that one entity applies or employs a particular modulation method or scheme in relation to another entity or process.
-
B.
usedOnMode
Indicates that something is applied, operated, or functions specifically in a given mode or operational setting.
-
C.
usesSignaling
Indicates that one entity communicates or coordinates with another by emitting, transmitting, or interpreting signals.
-
D.
canUse
Indicates that one entity has the ability, permission, or suitability to make use of another entity or resource.
-
E.
usesUniform
Indicates that one entity regularly wears or employs a standardized set of clothing or equipment designated as a uniform.
- 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_69a4948689d08190b3a4a3f388c02148 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf41c5d08190b07adbdb24d35a76 |
completed | March 1, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69a4bb696a38819095845c84f0241287 |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bce611ec819092cb13d354d0903e |
completed | March 1, 2026, 10:25 p.m. |
Created at: March 1, 2026, 7:47 p.m.