Triple
T6348804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | flag of Sierra Leone |
E142814
|
entity |
| Predicate | whiteSymbolismDetail |
P129
|
FINISHED |
| Object | desire for peace |
—
|
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: desire for peace | Statement: [flag of Sierra Leone, whiteSymbolismDetail, desire for peace]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: whiteSymbolismDetail Context triple: [flag of Sierra Leone, whiteSymbolismDetail, desire for peace]
-
A.
emblemSymbolism
Indicates that one entity serves as an emblem whose design or features symbolically represent or convey meanings about another entity.
-
B.
starColorSymbolism
Indicates how the color of a star is associated with particular symbolic meanings or themes.
-
C.
typicalMaterialSymbolism
Indicates that a material is commonly or characteristically used to symbolize or represent something in a given cultural or contextual setting.
-
D.
blackStripeSymbolism
Indicates the symbolic meaning or thematic significance associated with a black stripe in a given context.
-
E.
symbolizes
chosen
Indicates that one entity stands for, represents, or is used as a sign for another entity, concept, or idea.
- 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_69c008d6dcbc8190aa1c2f1fd8916b42 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c067bba1988190b51f0a22e4279e1b |
completed | March 22, 2026, 10:05 p.m. |
| PD | Predicate disambiguation | batch_69c060ea1a988190889e47b7e0c819b8 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:31 p.m.