Triple
T1850556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cross of the Order of Merit of the Federal Republic of Germany |
E41384
|
entity |
| Predicate | wearing |
P271
|
FINISHED |
| Object | on the left breast |
—
|
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: on the left breast | Statement: [Cross of the Order of Merit of the Federal Republic of Germany, wearing, on the left breast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wearing Context triple: [Cross of the Order of Merit of the Federal Republic of Germany, wearing, on the left breast]
-
A.
wears
chosen
Indicates that one entity is dressed in, or has on its body, a particular item such as clothing or accessories.
-
B.
wornAs
Indicates that one entity is used or put on as clothing, an accessory, or a wearable item by another entity.
-
C.
wearingMethod
Indicates the manner or method by which something is worn or put on.
-
D.
wornOver
Indicates that one item of clothing or accessory is positioned on top of and covering another item when worn.
-
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.
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_69a88648cd44819093303206d96d76ad |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb32d35508190bf1c487dffbecaf0 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafdca6d8819083c66f3a29fd9fd1 |
completed | March 7, 2026, 4:55 a.m. |
Created at: March 4, 2026, 7:33 p.m.