Triple
T11942999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Municipality of São Paulo |
E284223
|
entity |
| Predicate | governsTerritoryWithPopulation |
P14168
|
FINISHED |
| Object | over 10 million inhabitants |
—
|
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: over 10 million inhabitants | Statement: [Municipality of São Paulo, governsTerritoryWithPopulation, over 10 million inhabitants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: governsTerritoryWithPopulation Context triple: [Municipality of São Paulo, governsTerritoryWithPopulation, over 10 million inhabitants]
-
A.
governedPopulation
chosen
Indicates that one entity serves as the governing authority over the population of another entity.
-
B.
hasPopulationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
C.
countryWithKeyPopulation
Indicates that a country has a specific, particularly important or target population group that is being identified or highlighted.
-
D.
hasPopulationOver
Indicates that one entity has a population greater than a specified number or than another entity.
-
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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90342bb908190a019ac91a2b82f3d |
completed | April 10, 2026, 2:03 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3e48e08190b2fee43af4f57323 |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:45 p.m.