Triple
T4123119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | grand collier de la Légion d'honneur |
E92659
|
entity |
| Predicate | wearerRole |
P21359
|
FINISHED |
| Object | chef de l'État français |
—
|
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: chef de l'État français | Statement: [grand collier de la Légion d'honneur, wearerRole, chef de l'État français]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wearerRole Context triple: [grand collier de la Légion d'honneur, wearerRole, chef de l'État français]
-
A.
wearerType
Indicates the type or category of entity that is intended to wear or use the associated item.
-
B.
wearerStatus
chosen
Indicates the condition or role of an entity in its capacity as a wearer of something (e.g., clothing, equipment, or an accessory).
-
C.
wearerTitle
Indicates that a specified title or designation is held by the wearer of an item or garment.
-
D.
wearerEntitlement
Indicates that an entity has the right or authorization to wear a particular item (such as clothing, equipment, or an accessory).
-
E.
wearerDevice
Indicates that a device is worn or carried by a particular entity (the wearer).
- 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_69aed9685f70819086932777aec8d959 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69af0246e40081908ad6741a830ca68e |
completed | March 9, 2026, 5:24 p.m. |
| PD | Predicate disambiguation | batch_69af01867698819098e4144634b2ec4f |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:41 p.m.