Triple

T4722831
Position Surface form Disambiguated ID Type / Status
Subject Miami E104808 entity
Predicate UNUrbanAgglomerationCategory P40854 FINISHED
Object large urban agglomeration 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: large urban agglomeration | Statement: [Miami, UNUrbanAgglomerationCategory, large urban agglomeration]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: UNUrbanAgglomerationCategory
Context triple: [Miami, UNUrbanAgglomerationCategory, large urban agglomeration]
  • A. urbanAreaType
    Indicates the classification of an area based on its urban characteristics or development type (e.g., city, town, suburb, metropolitan region).
  • B. formsUrbanAreaWith
    Indicates that two or more settlements are geographically and functionally connected so that together they constitute a single continuous urban area.
  • C. hasUrbanClassification chosen
    Indicates that an entity is assigned a specific urban status or category within a defined classification system.
  • D. isUrbanCenter
    Indicates that a place functions as a primary, densely developed hub of population, services, and activities within a region.
  • E. urbanizationLevel
    Indicates the degree to which an area or population is characterized by urban development, infrastructure, and density of human settlement.
  • 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_69bd43ed84648190ae0b7ee8e8d00482 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd67c9c3c08190a6c4944cdd1362a8 completed March 20, 2026, 3:29 p.m.
PD Predicate disambiguation batch_69bd6220071881909670c89d072ffb6d completed March 20, 2026, 3:05 p.m.
Created at: March 20, 2026, 1:18 p.m.