Triple
T2670827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flag of Nigeria |
E55741
|
entity |
| Predicate | isVerticalTricolour |
P41590
|
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 Nigeria, isVerticalTricolour, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isVerticalTricolour Context triple: [Flag of Nigeria, isVerticalTricolour, true]
-
A.
nationalFlagColor
Indicates that a specific color appears on the national flag of a given country.
-
B.
ribbonColours
Indicates that there is an association between an entity and one or more colours of ribbons related to it.
-
C.
isWarEnsignOf
Indicates that one entity is the war ensign (a specific military or wartime flag) representing or belonging to another entity.
-
D.
isCivilEnsignOf
Indicates that an object is the civil (non-military) ensign or flag officially used to represent a particular entity, typically a country or territory.
-
E.
numberOfGoldStripes
Indicates the specific count of gold-colored stripes associated with an entity.
- 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_69ab49e54de48190be708cd1cf8be073 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd98e7d00819088398206fc7db477 |
completed | March 7, 2026, 7:53 a.m. |
| PD | Predicate disambiguation | batch_69abd8190ad481908f3e14ac84d0940a |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd8f98c348190a68064c565589459 |
completed | March 7, 2026, 7:51 a.m. |
Created at: March 6, 2026, 9:54 p.m.