Triple
T226969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European Union |
E4332
|
entity |
| Predicate | hasPopulationApprox |
P3412
|
FINISHED |
| Object | 450 million |
—
|
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: 450 million | Statement: [European Union, hasPopulationApprox, 450 million]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPopulationApprox Context triple: [European Union, hasPopulationApprox, 450 million]
-
A.
hasPopulationApproximate
chosen
Indicates that an entity has an estimated or approximate population size, rather than an exact count.
-
B.
hasPopulationAsOf
Indicates that a population count is associated with a specific point or date in time when that population figure was valid or recorded.
-
C.
metropolitanAreaPopulationApproximate
Indicates that the predicate specifies an approximate total population size for a given metropolitan area.
-
D.
hasPopulationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
E.
hasPopulationDensity
Indicates the number of individuals (e.g., people, organisms) per unit area associated with a given entity or region.
- 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_69a257363ffc81909757bde7ab3404da |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25d10ac248190a98dedabf5358668 |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b5877588190af694d060377f027 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.