Triple
T2176704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Cross with Collar |
E48544
|
entity |
| Predicate | collarWorn |
P11705
|
FINISHED |
| Object | around the neck over the shoulders |
—
|
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: around the neck over the shoulders | Statement: [Grand Cross with Collar, collarWorn, around the neck over the shoulders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collarWorn Context triple: [Grand Cross with Collar, collarWorn, around the neck over the shoulders]
-
A.
wornAround
chosen
Indicates that one entity is physically worn encircling or surrounding another entity (e.g., around a body part or object).
-
B.
supporterCollar
Indicates that one entity serves as a collar-like structural element that supports or stabilizes another entity.
-
C.
hasInsigniaWornBy
Indicates that a particular insignia is worn by a specified entity (such as a person, group, or organization).
-
D.
wearerStatus
Indicates the condition or role of an entity in its capacity as a wearer of something (e.g., clothing, equipment, or an accessory).
-
E.
wearClassification
Indicates a classification relationship specifying the type or category of wear associated with an entity or interaction.
- 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_69a88aa3faa48190995b233af6525815 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc4358fc88190a6f556c2de9fef8c |
completed | March 7, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69abbda0ec948190be88c1243d81a423 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:45 p.m.