Triple
T742657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Combat Infantryman Badge |
E15275
|
entity |
| Predicate | wearLocation |
P18894
|
FINISHED |
| Object | above left breast pocket on U.S. Army uniform |
—
|
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: above left breast pocket on U.S. Army uniform | Statement: [Combat Infantryman Badge, wearLocation, above left breast pocket on U.S. Army uniform]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wearLocation Context triple: [Combat Infantryman Badge, wearLocation, above left breast pocket on U.S. Army uniform]
-
A.
wears
Indicates that one entity is dressed in, or has on its body, a particular item such as clothing or accessories.
-
B.
wornAround
Indicates that one entity is physically worn encircling or surrounding another entity (e.g., around a body part or object).
-
C.
individualWear
Indicates that an individual is wearing or has clothing or an accessory on their body.
-
D.
wearingClass
Indicates that one entity is wearing or dressed in an item belonging to a particular class or category of clothing or accessories.
-
E.
wearingMethod
Indicates the manner or method by which something is worn or put on.
- 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_69a49358aa308190adbc9b5a0a2adcf9 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a60f92d08190a4f44c5b4d068ab5 |
completed | March 1, 2026, 8:48 p.m. |
| PD | Predicate disambiguation | batch_69a4a4fdaaf48190985f62acfc069508 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a5a35c68819082429755c046e9a7 |
completed | March 1, 2026, 8:46 p.m. |
Created at: March 1, 2026, 7:37 p.m.