Triple

T17126581
Position Surface form Disambiguated ID Type / Status
Subject Belgium and the Netherlands E415611 entity
Predicate shareUrbanPattern P37688 FINISHED
Object high urbanization levels 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: high urbanization levels | Statement: [Belgium and the Netherlands, shareUrbanPattern, high urbanization levels]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: shareUrbanPattern
Context triple: [Belgium and the Netherlands, shareUrbanPattern, high urbanization levels]
  • A. hasUrbanFabric
    Indicates that one entity possesses, contains, or is characterized by a particular pattern or structure of built-up urban development.
  • B. urbanDesign
    Indicates the relationship in which an entity is responsible for planning, organizing, or shaping the physical layout and functional structure of urban spaces.
  • C. urbanMorphology chosen
    Indicates the spatial form, structure, and layout relationships that characterize the physical configuration of an urban area.
  • D. isUrbanForm
    Indicates that an entity represents or exhibits characteristics of an urban built environment or city-like spatial structure.
  • E. isUrbanSee
    Indicates a relationship where a location or area is recognized or classified as an urban settlement or city-like 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_69d886d090cc8190a39cb94992586905 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f027a3d081908fc1134b50db3d45 completed April 18, 2026, 8:57 p.m.
PD Predicate disambiguation batch_69e3830192ac819091344a9e5a36c8c9 completed April 18, 2026, 1:11 p.m.
Created at: April 10, 2026, 5:36 a.m.