Triple
T4536497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thessaloniki (regional unit) |
E107419
|
entity |
| Predicate | hasUrbanRuralComposition |
P24917
|
FINISHED |
| Object | urban areas |
—
|
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: urban areas | Statement: [Thessaloniki (regional unit), hasUrbanRuralComposition, urban areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUrbanRuralComposition Context triple: [Thessaloniki (regional unit), hasUrbanRuralComposition, urban areas]
-
A.
hasUrbanRuralMix
chosen
Indicates that something exhibits a combination or blend of both urban and rural characteristics or components.
-
B.
urbanRuralSplit
Indicates a division or distinction between urban and rural areas, conditions, or populations.
-
C.
hasUrbanClassification
Indicates that an entity is assigned a specific urban status or category within a defined classification system.
-
D.
isUrbanized
Indicates that a place or area has been developed with dense human settlement, infrastructure, and built environment characteristic of a city or town.
-
E.
hasUrbanFunction
Indicates that an entity serves a specific role or purpose within an urban context, such as providing services, infrastructure, or activities typical of a city environment.
- 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_69bd43f922788190b7edfa294e39b178 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57b78b8481909d79131723d4be22 |
completed | March 20, 2026, 2:20 p.m. |
| PD | Predicate disambiguation | batch_69bd521edd00819099dfccaa65dddd61 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:04 p.m.