Triple
T374054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Croix de la Légion d'honneur |
E8330
|
entity |
| Predicate | wearingOccasion |
P2934
|
FINISHED |
| Object | state ceremonies |
—
|
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: state ceremonies | Statement: [Grand Croix de la Légion d'honneur, wearingOccasion, state ceremonies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wearingOccasion Context triple: [Grand Croix de la Légion d'honneur, wearingOccasion, state ceremonies]
-
A.
wears
Indicates that one entity is dressed in, or has on its body, a particular item such as clothing or accessories.
-
B.
displayOccasion
chosen
Indicates the event, context, or situation during which something is presented, shown, or made visible.
-
C.
primaryOccasion
Indicates that one occasion is the main or most significant event associated with a given context, entity, or activity.
-
D.
individualWear
Indicates that an individual is wearing or has clothing or an accessory on their body.
-
E.
hasDressCode
Indicates that a specified entity enforces or is associated with a particular set of rules governing appropriate clothing or attire.
- 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_69a2e7f2ec648190b42bc7db424f8109 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec13b9b48190b294d998c6720132 |
completed | Feb. 28, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69a2e96216048190873ae533fa5b864d |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.