Triple

T24798775
Position Surface form Disambiguated ID Type / Status
Subject Myeon E620462 entity
Predicate hasHigherUrbanizationThan P159688 FINISHED
Object none 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: none | Statement: [Myeon, hasHigherUrbanizationThan, none]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasHigherUrbanizationThan
Context triple: [Myeon, hasHigherUrbanizationThan, none]
  • A. hasHighestUrbanizationRateIn
    Indicates that the subject has the greatest proportion of its population living in urban areas compared to all other entities within the specified object region or group.
  • B. isHighlyUrbanizedCity
    Indicates that a city has a very high level of urban development, density, and built-up infrastructure relative to typical cities.
  • C. isHighlyUrbanizedCityOf
    Indicates that a city is characterized by a high degree of urban development and population density within the specified larger region or jurisdiction.
  • D. isUrbanizedAround
    Indicates that an area or region has developed urban characteristics or infrastructure surrounding a particular location or feature.
  • 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. chosen

Provenance (4 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_69e2fabe77c8819085f7ce6486248139 completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f5f7a205688190b8f36bff5013247c completed May 2, 2026, 1:09 p.m.
PD Predicate disambiguation batch_69f5afd5baac8190bb8ed576813c8591 completed May 2, 2026, 8:03 a.m.
PDg Predicate description generation batch_69f5f6b32a8881909baa0db57b80d56a completed May 2, 2026, 1:05 p.m.
Created at: April 18, 2026, 4:49 a.m.