Triple
T30180700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Air Force beret |
E767191
|
entity |
| Predicate | hasStandardWear |
P125675
|
FINISHED |
| Object | tilted to the right |
—
|
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: tilted to the right | Statement: [Royal Air Force beret, hasStandardWear, tilted to the right]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStandardWear Context triple: [Royal Air Force beret, hasStandardWear, tilted to the right]
-
A.
typeOfWear
chosen
Indicates the specific manner or style in which something is worn or used as clothing or adornment.
-
B.
wornUntil
Indicates that an item of clothing or wearable object was used or worn continuously up to a specific time or event.
-
C.
orderOfWear
Indicates the relative sequence in which items are intended to be worn, specifying which item is put on before or after another.
-
D.
wornFor
Indicates that an item is worn for a particular purpose, function, or occasion.
-
E.
wears
Indicates that one entity is dressed in, or has on its body, a particular item such as clothing or accessories.
- 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_69f2247ba20c81909d34f2bfed706e1e |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fe21b0cba48190b56c39e9f1c0eafa |
completed | May 8, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_69fe204576848190aecf204e2adba5dc |
completed | May 8, 2026, 5:41 p.m. |
Created at: April 29, 2026, 7:26 p.m.