Triple
T2304429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Order of the White Lion |
E51804
|
entity |
| Predicate | wearerTitle |
P39062
|
FINISHED |
| Object | Knight of the Order of the White Lion |
—
|
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: Knight of the Order of the White Lion | Statement: [Order of the White Lion, wearerTitle, Knight of the Order of the White Lion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wearerTitle Context triple: [Order of the White Lion, wearerTitle, Knight of the Order of the White Lion]
-
A.
wearerStatus
Indicates the condition or role of an entity in its capacity as a wearer of something (e.g., clothing, equipment, or an accessory).
-
B.
wearerEntitlement
Indicates that an entity has the right or authorization to wear a particular item (such as clothing, equipment, or an accessory).
-
C.
wearerDevice
Indicates that a device is worn or carried by a particular entity (the wearer).
-
D.
wears
Indicates that one entity is dressed in, or has on its body, a particular item such as clothing or accessories.
-
E.
wearingClass
Indicates that one entity is wearing or dressed in an item belonging to a particular class or category of clothing or accessories.
- 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_69a88b0bb30c81908ded03b006d29387 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abce1f4f0c8190a714e4dcb8449f7e |
completed | March 7, 2026, 7:05 a.m. |
| PD | Predicate disambiguation | batch_69abc58ce2a081908ce2f0cadd92e9f8 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abce1e7c788190a15890feb2437f1d |
completed | March 7, 2026, 7:05 a.m. |
Created at: March 4, 2026, 7:49 p.m.