Triple

T6147202
Position Surface form Disambiguated ID Type / Status
Subject Ilha Joana Bezerra E137107 entity
Predicate urbanPlanningIssues P32029 FINISHED
Object flood risk 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: flood risk | Statement: [Ilha Joana Bezerra, urbanPlanningIssues, flood risk]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: urbanPlanningIssues
Context triple: [Ilha Joana Bezerra, urbanPlanningIssues, flood risk]
  • A. urbanPlanningFunction
    Indicates a functional role or purpose that something serves within the planning, organization, or management of urban spaces and infrastructure.
  • B. urbanDevelopment
    Indicates the process or activities through which urban areas are planned, expanded, or transformed, including changes to infrastructure, land use, and the built environment.
  • C. hasUrbanPlanning
    Indicates that an entity is involved in, responsible for, or characterized by activities or attributes related to urban planning.
  • D. mainUrbanPlan
    Indicates the primary urban planning scheme or framework that governs the development and organization of a given area.
  • E. hasUrbanIssue chosen
    Indicates that an entity experiences, is affected by, or is associated with a specific problem or challenge related to urban environments or city life.
  • 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_69c008a2c6308190a56519b22d55d083 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05cdeeaa88190948d9db6eb2dbf46 completed March 22, 2026, 9:19 p.m.
PD Predicate disambiguation batch_69c055f39e0881909ae56444b1b48929 completed March 22, 2026, 8:49 p.m.
Created at: March 22, 2026, 4:16 p.m.