Triple
T24548715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Castello d’Argile |
E607296
|
entity |
| Predicate | hasUrbanRuralProfile |
P60791
|
FINISHED |
| Object | predominantly rural |
—
|
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: predominantly rural | Statement: [Castello d’Argile, hasUrbanRuralProfile, predominantly rural]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUrbanRuralProfile Context triple: [Castello d’Argile, hasUrbanRuralProfile, predominantly rural]
-
A.
isRuralOrUrban
chosen
Indicates whether an entity is classified as being in a rural area or an urban area.
-
B.
hasUrbanPopulationIn
Indicates that an entity has a specified urban population within a particular geographic area or administrative unit.
-
C.
hasUrbanClassification
Indicates that an entity is assigned a specific urban status or category within a defined classification system.
-
D.
hasUrbanRuralMix
Indicates that something exhibits a combination or blend of both urban and rural characteristics or components.
-
E.
isUrbanizedAround
Indicates that an area or region has developed urban characteristics or infrastructure surrounding a particular location or feature.
- 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_69e2c4c9bf94819082d05da6f5c29907 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a8cb6dc081909bf37123d82ed2c9 |
completed | April 30, 2026, 12:56 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b99e7c8190ba7e2dc8729a314a |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:27 a.m.