Triple
T37694927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | flag of Equatorial Guinea |
E938901
|
entity |
| Predicate | redIsPanAfricanColor |
P189143
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [flag of Equatorial Guinea, redIsPanAfricanColor, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: redIsPanAfricanColor Context triple: [flag of Equatorial Guinea, redIsPanAfricanColor, true]
-
A.
usesPanAfricanColors
Indicates that one entity employs or incorporates the Pan-African colors (typically red, black, green, and sometimes yellow) in relation to another entity.
-
B.
isPanAfricanSymbol
Indicates that something functions as a symbol representing Pan-African identity, unity, or solidarity across African peoples and the African diaspora.
-
C.
redColorRepresents
Indicates that one entity uses the color red to symbolize, denote, or stand for another entity or concept.
-
D.
redPrimary_x
Indicates that the subject has red as its primary or dominant color.
-
E.
redPrimary_y
Indicates that the entity has red as its primary or dominant color.
- F. None of above. chosen
Provenance (4 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_69f76eda6ae48190b3111071eeacc038 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbb084760c8190a1554985d3c3cb7a |
completed | May 6, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_69fbadf3cb548190ba3b7514f76b790a |
completed | May 6, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69fbb083ab708190a18b045311106f27 |
completed | May 6, 2026, 9:20 p.m. |
Created at: May 3, 2026, 4:18 p.m.