Triple

T3768043
Position Surface form Disambiguated ID Type / Status
Subject Ville Nouvelle (Fez) E82726 entity
Predicate hasUrbanDensity P9969 FINISHED
Object medium to high 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: medium to high | Statement: [Ville Nouvelle (Fez), hasUrbanDensity, medium to high]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasUrbanDensity
Context triple: [Ville Nouvelle (Fez), hasUrbanDensity, medium to high]
  • A. isUrbanized
    Indicates that a place or area has been developed with dense human settlement, infrastructure, and built environment characteristic of a city or town.
  • B. urbanizationLevel chosen
    Indicates the degree to which an area or population is characterized by urban development, infrastructure, and density of human settlement.
  • C. hasUrbanFunction
    Indicates that an entity serves a specific role or purpose within an urban context, such as providing services, infrastructure, or activities typical of a city environment.
  • D. statusInUrbanAreas
    Indicates the condition, prevalence, or situation of something specifically within urban areas.
  • E. isUrbanizing
    Indicates a process in which an area or population becomes more urban in character, typically through increased development, infrastructure, and concentration of people and activities.
  • 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_69ad8b207b0081909d2b48843fbd8795 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcc2bdf6c819088d3c6ace83ca5ea completed March 8, 2026, 7:21 p.m.
PD Predicate disambiguation batch_69adc04ec36c8190bd5b944d4f4d32aa completed March 8, 2026, 6:30 p.m.
Created at: March 8, 2026, 3:35 p.m.