Triple
T20467659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | War Merit Cross 1st Class with Swords |
E502095
|
entity |
| Predicate | wearMethod |
P14609
|
FINISHED |
| Object | pin-back mounting |
—
|
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: pin-back mounting | Statement: [War Merit Cross 1st Class with Swords, wearMethod, pin-back mounting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wearMethod Context triple: [War Merit Cross 1st Class with Swords, wearMethod, pin-back mounting]
-
A.
wearClassification
Indicates a classification relationship specifying the type or category of wear associated with an entity or interaction.
-
B.
wearLocation
Indicates the typical body part or location on which an item is worn.
-
C.
wearIndicates
Indicates that one entity is wearing or has clothing or an accessory on its body, typically as a visible or functional item.
-
D.
wearingMethod
chosen
Indicates the manner or method by which something is worn or put on.
-
E.
wearerType
Indicates the type or category of entity that is intended to wear or use the associated item.
- 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_69e0b4ae5f1081908768b0c9a3a0bf38 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6995d9d1c81909ee223a35a0850ba |
completed | April 20, 2026, 9:23 p.m. |
| PD | Predicate disambiguation | batch_69e57679eb40819086142df3e39c928e |
completed | April 20, 2026, 12:42 a.m. |
Created at: April 16, 2026, 11:33 a.m.