Triple
T16168714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rashaida |
E392375
|
entity |
| Predicate | dressSymbolism |
P38168
|
FINISHED |
| Object | marker of group identity |
—
|
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: marker of group identity | Statement: [Rashaida, dressSymbolism, marker of group identity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dressSymbolism Context triple: [Rashaida, dressSymbolism, marker of group identity]
-
A.
clothingSymbolism
chosen
Indicates how clothing or attire conveys symbolic meaning, such as status, identity, emotion, or cultural significance, within a given context.
-
B.
shapeSymbolism
Indicates how a particular shape is associated with or conveys symbolic meaning within a given context.
-
C.
emblemSymbolism
Indicates that one entity serves as an emblem whose design or features symbolically represent or convey meanings about another entity.
-
D.
typicalMaterialSymbolism
Indicates that a material is commonly or characteristically used to symbolize or represent something in a given cultural or contextual setting.
-
E.
symbolismIn
Indicates that one entity functions as a symbol or representation within the context, meaning, or interpretive framework of another entity.
- 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_69d87f1d32208190942e4e499a80c18c |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21eb5e6d881908749683091afa90c |
completed | April 17, 2026, 11:51 a.m. |
| PD | Predicate disambiguation | batch_69e219d642708190ba31a90dce76a210 |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:02 a.m.