Triple
T1005080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Cross |
E21689
|
entity |
| Predicate | rankInOrderOfWear |
P16982
|
FINISHED |
| Object | second only to 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: second only to Victoria Cross | Statement: [George Cross, rankInOrderOfWear, second only to Victoria Cross]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankInOrderOfWear Context triple: [George Cross, rankInOrderOfWear, second only to Victoria Cross]
-
A.
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).
-
B.
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.
-
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.
wornAt
Indicates that an item is being worn on a specific part of the body or at a particular time or event.
- 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_69a493c53e648190ae8cb76c433fd9a7 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b51303548190a5ee3c0797fc3245 |
completed | March 1, 2026, 9:52 p.m. |
| PD | Predicate disambiguation | batch_69a4b2b2e7108190b338b6c19d4aff55 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:41 p.m.