Triple

T20879786
Position Surface form Disambiguated ID Type / Status
Subject European Metropolitan Regions in Germany E514113 entity
Predicate spatialPlanningLevel P33672 FINISHED
Object national 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: national | Statement: [European Metropolitan Regions in Germany, spatialPlanningLevel, national]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: spatialPlanningLevel
Context triple: [European Metropolitan Regions in Germany, spatialPlanningLevel, national]
  • A. urbanPlanningLevel
    Indicates the degree or quality of planning, organization, and regulation applied to the development and use of urban spaces.
  • B. hasPlanningLevel chosen
    Indicates that an entity is associated with a specific stage, tier, or granularity within a planning or scheduling hierarchy.
  • C. spatialHierarchy
    Indicates a spatial relationship in which one entity is positioned within, above, below, or otherwise hierarchically organized relative to another in physical space.
  • D. planningControl
    Indicates that an authority or agent exercises regulatory oversight or decision-making power over how something is planned, developed, or used.
  • E. spatialProperty
    Indicates a relationship where one entity has a specific spatial characteristic, such as position, size, orientation, or geometric configuration in space, relative to a reference frame or other entities.
  • 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_69e0b4f733f081908a401c0b7beb0b9f completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c678b394819096a17de9e04cd74f completed April 21, 2026, 12:36 a.m.
PD Predicate disambiguation batch_69e5c9a8dc148190b33ff51894e2a8f9 completed April 20, 2026, 6:37 a.m.
Created at: April 16, 2026, 12:45 p.m.