Triple
T3993392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Conspicuous Gallantry Cross |
E87042
|
entity |
| Predicate | orderOfWearUK |
P16982
|
FINISHED |
| Object | immediately below the Victoria Cross |
—
|
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: immediately below the Victoria Cross | Statement: [Conspicuous Gallantry Cross, orderOfWearUK, immediately below the Victoria Cross]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: orderOfWearUK Context triple: [Conspicuous Gallantry Cross, orderOfWearUK, immediately below the Victoria Cross]
-
A.
orderOfWearInUK
chosen
Indicates the sequence or priority in which items are worn in the UK context (e.g., clothing or insignia), relative to other items.
-
B.
wearingOrder
Indicates the relative sequence in which items are worn on or over one another (e.g., which garment is worn over or under another).
-
C.
wornFor
Indicates that an item is worn for a particular purpose, function, or occasion.
-
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.
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_69aed94118148190975e6aa4e554cde9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb81040481909b22e4c445ecae0f |
completed | March 9, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69aef8f692008190bf4d637ffc3d3eaa |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:33 p.m.