Triple
T6348805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | flag of Sierra Leone |
E142814
|
entity |
| Predicate | greenSymbolismDetail |
P38847
|
FINISHED |
| Object | agricultural and mineral wealth |
—
|
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: agricultural and mineral wealth | Statement: [flag of Sierra Leone, greenSymbolismDetail, agricultural and mineral wealth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: greenSymbolismDetail Context triple: [flag of Sierra Leone, greenSymbolismDetail, agricultural and mineral wealth]
-
A.
starColorSymbolism
Indicates how the color of a star is associated with particular symbolic meanings or themes.
-
B.
emblemSymbolism
Indicates that one entity serves as an emblem whose design or features symbolically represent or convey meanings about another entity.
-
C.
greenRepresents
chosen
Indicates that one entity uses the color green to symbolize, denote, or stand for another entity or concept.
-
D.
greenFieldSymbolizes
Indicates that a green field is used as a symbol representing or conveying a particular idea, quality, or concept.
-
E.
flowerSymbolMeaning
Indicates that a particular flower is used to represent or convey a specific symbolic meaning or message.
- 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.