Triple
T480118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abuja |
E9148
|
entity |
| Predicate | populationGrowth |
P3837
|
FINISHED |
| Object | one of the fastest-growing cities in Africa |
—
|
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: one of the fastest-growing cities in Africa | Statement: [Abuja, populationGrowth, one of the fastest-growing cities in Africa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationGrowth Context triple: [Abuja, populationGrowth, one of the fastest-growing cities in Africa]
-
A.
populationIncrease
chosen
Indicates that the number of individuals in a population has grown over a specified period of time.
-
B.
population
Indicates the total number of individuals living in or present within a specified area or group.
-
C.
populationDensity
Indicates the number of individuals or entities occupying a unit area within a given region.
-
D.
currentPopulation
Indicates the present number of individuals living in or belonging to a specified entity (such as a location or group).
-
E.
hasPopulationAsOf
Indicates that a population count is associated with a specific point or date in time when that population figure was valid or recorded.
- 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_69a2e7ff81708190b0507a24a997232c |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f057c4ac819080cf43ffaa56c350 |
completed | Feb. 28, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69a2edf1d5848190a7da27e2fddc136f |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.