Triple
T32597654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mossi people |
E833265
|
entity |
| Predicate | estimatedShareOfBurkinaPopulation |
P178784
|
FINISHED |
| Object | about half |
—
|
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: about half | Statement: [Mossi people, estimatedShareOfBurkinaPopulation, about half]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedShareOfBurkinaPopulation Context triple: [Mossi people, estimatedShareOfBurkinaPopulation, about half]
-
A.
populationRankInBurkinaFaso
Indicates the relative position of an entity in terms of population size compared to other entities within Burkina Faso.
-
B.
statusInBurkinaFaso
Indicates the legal, social, or official condition or standing that an entity has within the context of Burkina Faso.
-
C.
populationShareOfCountry
chosen
Indicates the proportion of a country’s total population that is accounted for by a specified subpopulation or region.
-
D.
demographicStatusInCoteDIvoire
Indicates the demographic status or classification of an entity within the context of Côte d’Ivoire.
-
E.
dividedPopulationOf
Indicates that a population has been split into distinct subgroups or segments, typically based on specified criteria or characteristics.
- 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_69f3492ab63c8190aec24d5003b47c29 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f7308a096081909d66a56f3c926806 |
completed | May 3, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69f72a00c5f081908b6539d15baf4e12 |
completed | May 3, 2026, 10:57 a.m. |
Created at: May 1, 2026, 1:05 a.m.