Triple
T12429196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Honour Cross of the World War 1914/1918 |
E296980
|
entity |
| Predicate | typicalWear |
P104877
|
FINISHED |
| Object | on ribbon on 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 ribbon on left breast | Statement: [Honour Cross of the World War 1914/1918, typicalWear, on ribbon on left breast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalWear Context triple: [Honour Cross of the World War 1914/1918, typicalWear, on ribbon on left breast]
-
A.
typicallyWornBy
Indicates that something (such as an item or garment) is most commonly or characteristically worn by a particular type of person or group.
-
B.
typicallyWornWith
Indicates that one item of clothing or accessory is commonly or customarily worn together with another.
-
C.
wears
Indicates that one entity is dressed in, or has on its body, a particular item such as clothing or accessories.
-
D.
wearingClass
Indicates that one entity is wearing or dressed in an item belonging to a particular class or category of clothing or accessories.
-
E.
individualWear
Indicates that an individual is wearing or has clothing or an accessory on their body.
- 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_69d6ada0640c81908c061d7fb3d47786 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94df948308190ace333230a4a3b38 |
completed | April 10, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_69d94d391c548190996a8c698357f273 |
completed | April 10, 2026, 7:19 p.m. |
| PDg | Predicate description generation | batch_69d94df652cc8190a1d2d685fa87cf98 |
completed | April 10, 2026, 7:22 p.m. |
Created at: April 8, 2026, 9:55 p.m.