Triple
T24384885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USMMA |
E614717
|
entity |
| Predicate | grantsCommission |
P156001
|
FINISHED |
| Object | U.S. Navy Reserve officer commission (for eligible graduates) |
—
|
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: U.S. Navy Reserve officer commission (for eligible graduates) | Statement: [USMMA, grantsCommission, U.S. Navy Reserve officer commission (for eligible graduates)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grantsCommission Context triple: [USMMA, grantsCommission, U.S. Navy Reserve officer commission (for eligible graduates)]
-
A.
grantsAre
Indicates that one entity provides or awards grants to another entity.
-
B.
grantsRecognitionTo
Indicates that one entity formally acknowledges, honors, or validates another entity’s achievements, status, or contributions.
-
C.
grantsForm
Indicates that one entity provides or issues an official form or document to another entity.
-
D.
notableGrant
Indicates that an entity has received a grant or funding award that is considered significant or noteworthy.
-
E.
compilationCommission
Indicates that an entity is responsible for overseeing or managing the compilation or assembly of another entity (such as a work, collection, or dataset).
- 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_69e2d7e362e481909e32fe4ef8269d4f |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f294540000819099bacb398a36204f |
completed | April 29, 2026, 11:29 p.m. |
| PD | Predicate disambiguation | batch_69f287c4a2b48190b80fb7a3c0e9b018 |
completed | April 29, 2026, 10:35 p.m. |
| PDg | Predicate description generation | batch_69f28f4d978c81908310c01def2514cc |
completed | April 29, 2026, 11:07 p.m. |
Created at: April 18, 2026, 2:03 a.m.