Triple
T2183525
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Afro-Mexicans |
E49099
|
entity |
| Predicate | populationShare2020 |
P32997
|
FINISHED |
| Object | around 2 percent of Mexico’s population |
—
|
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: around 2 percent of Mexico’s population | Statement: [Afro-Mexicans, populationShare2020, around 2 percent of Mexico’s population]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationShare2020 Context triple: [Afro-Mexicans, populationShare2020, around 2 percent of Mexico’s population]
-
A.
hasPopulationAsOf
Indicates that a population count is associated with a specific point or date in time when that population figure was valid or recorded.
-
B.
populationDemonym
Indicates the term used to refer to the people or inhabitants associated with a particular place or region.
-
C.
populationCount
chosen
Indicates the total number of individuals in a specified group, area, or category.
-
D.
populationIncludes
Indicates that a population contains or encompasses the specified individual(s) or subgroup(s) as members or elements.
-
E.
countryPopulationContext
Indicates the contextual population characteristics or statistics associated with a specific country.
- 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_69a88aa72d348190a9544bb5b8a4e71d |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc4358fc88190a6f556c2de9fef8c |
completed | March 7, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69abbda0ec948190be88c1243d81a423 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:45 p.m.