Triple
T16444423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cross of Merit 1st Class |
E399386
|
entity |
| Predicate | isDecorationOf |
P37287
|
FINISHED |
| Object | national order of merit of Germany |
—
|
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: national order of merit of Germany | Statement: [Cross of Merit 1st Class, isDecorationOf, national order of merit of Germany]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isDecorationOf Context triple: [Cross of Merit 1st Class, isDecorationOf, national order of merit of Germany]
-
A.
containsDecorationFrom
Indicates that one entity includes or incorporates a decorative element that originates from another entity.
-
B.
relatedDecoration
chosen
Indicates that one decoration is associated with, complements, or is contextually linked to another decoration.
-
C.
hasDecor
Indicates that one entity possesses, features, or is adorned with a particular decorative element or style.
-
D.
typeOfDecoration
Indicates the specific kind or style of decoration associated with an entity or applied in a given context.
-
E.
isNonCombatDecoration
Indicates that an award or decoration is given for non-combat service or achievements rather than for participation in direct combat.
- 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_69d87f2c6778819080fcfae53be8f12a |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32cd9d474819091b4a80de1019c54 |
completed | April 18, 2026, 7:03 a.m. |
| PD | Predicate disambiguation | batch_69e227048d608190a4205eae3117629a |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:10 a.m.