Triple

T5037622
Position Surface form Disambiguated ID Type / Status
Subject N'Djamena E113463 entity
Predicate urbanAgglomerationType P749 FINISHED
Object metropolitan area 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: metropolitan area | Statement: [N'Djamena, urbanAgglomerationType, metropolitan area]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: urbanAgglomerationType
Context triple: [N'Djamena, urbanAgglomerationType, metropolitan area]
  • A. urbanAreaType chosen
    Indicates the classification of an area based on its urban characteristics or development type (e.g., city, town, suburb, metropolitan region).
  • B. urbanDistrictType
    Indicates the classification of an urban district according to its specific type or category within an administrative or planning system.
  • C. metropolitanAreaType
    Indicates the classification of a metropolitan area according to its type or category (e.g., size, function, or administrative status).
  • D. formsUrbanAreaWith
    Indicates that two or more settlements are geographically and functionally connected so that together they constitute a single continuous urban area.
  • 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_69bd44384298819089c49e7c330ec7b8 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73daaa788190b670f6c328bfa44f completed March 20, 2026, 4:20 p.m.
PD Predicate disambiguation batch_69bd71529d608190a53470ba6c14bb1d completed March 20, 2026, 4:09 p.m.
Created at: March 20, 2026, 1:37 p.m.