Triple
T652985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS-Obersturmbannführer |
E11383
|
entity |
| Predicate | uniformContext |
P2919
|
FINISHED |
| Object | black SS uniform |
—
|
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: black SS uniform | Statement: [SS-Obersturmbannführer, uniformContext, black SS uniform]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: uniformContext Context triple: [SS-Obersturmbannführer, uniformContext, black SS uniform]
-
A.
canonicalContext
Indicates the standard or primary contextual framework within which an entity, statement, or resource is to be interpreted.
-
B.
usesUniform
Indicates that one entity regularly wears or employs a standardized set of clothing or equipment designated as a uniform.
-
C.
contextOf
chosen
Indicates that one entity provides the situational, informational, or environmental background within which another entity exists, occurs, or is interpreted.
-
D.
uniformDistinction
Indicates that a clear and consistent difference is maintained between two or more entities within a given context.
-
E.
context
Indicates that one entity provides the surrounding circumstances, setting, or background within which another entity, event, or statement occurs or is interpreted.
- 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_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f4a660c8190b887cb4da01ef7ae |
completed | March 1, 2026, 8:19 p.m. |
| PD | Predicate disambiguation | batch_69a49d1001088190aa7ca3c8f2ad0e32 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.