Triple
T853642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meritorious Unit Commendation |
E18441
|
entity |
| Predicate | individualWearAuthorized |
P20626
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Meritorious Unit Commendation, individualWearAuthorized, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: individualWearAuthorized Context triple: [Meritorious Unit Commendation, individualWearAuthorized, true]
-
A.
individualWear
Indicates that an individual is wearing or has clothing or an accessory on their body.
-
B.
wearerDevice
Indicates that a device is worn or carried by a particular entity (the wearer).
-
C.
hasInsigniaWornBy
Indicates that a particular insignia is worn by a specified entity (such as a person, group, or organization).
-
D.
authorizedHeadgear
Indicates that a particular item of headgear is officially permitted or approved for use in a given context or by a specific authority.
-
E.
wearLocation
Indicates the typical body part or location on which an item is worn.
- 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_69a4938bdd3c8190a954a3c11844d9cf |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac389a44819093396a58d2afa700 |
completed | March 1, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69a4aa81ef348190b067f817574e9efe |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4ab4893e481908632102d240466dc |
completed | March 1, 2026, 9:10 p.m. |
Created at: March 1, 2026, 7:39 p.m.