Triple
T18583926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viareggini |
E454189
|
entity |
| Predicate | urbanPopulation |
P560
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Viareggini, urbanPopulation, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: urbanPopulation Context triple: [Viareggini, urbanPopulation, true]
-
A.
hasUrbanPopulationIn
Indicates that an entity has a specified urban population within a particular geographic area or administrative unit.
-
B.
permanentPopulation
Indicates that an entity has a stable, long-term resident population rather than a temporary or transient presence.
-
C.
populationFocus
Indicates that something is primarily directed toward, concerned with, or designed for a particular population or demographic group.
-
D.
cityPopulationContext
chosen
Indicates the contextual relationship between a city and information about its population, such as size, distribution, or demographic characteristics.
-
E.
metroPopulationContext
Indicates that the population value is measured or interpreted specifically within the context of a metropolitan area (metro region) rather than another geographic or administrative unit.
- 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e543d200dc8190b8797d731f4e4865 |
completed | April 19, 2026, 9:06 p.m. |
| PD | Predicate disambiguation | batch_69e478c98d4c81909d37a0e72c6e7bd0 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:44 a.m.