Triple

T1586659
Position Surface form Disambiguated ID Type / Status
Subject Busanjin District E34080 entity
Predicate hasSubdivisionsType P9832 FINISHED
Object administrative dong 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: administrative dong | Statement: [Busanjin District, hasSubdivisionsType, administrative dong]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasSubdivisionsType
Context triple: [Busanjin District, hasSubdivisionsType, administrative dong]
  • A. hasSubdivision
    Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
  • B. hasSubdivisionCode
    Indicates that an entity is associated with a specific code identifying one of its internal subdivisions (such as a state, province, or region).
  • C. hasSubregionStatus
    Indicates that one region holds an official or defined status as a subregion within a larger geographic or administrative area.
  • D. representsSubdivisionOf
    Indicates that one administrative or territorial unit is a smaller, constituent part of a larger administrative or territorial unit.
  • E. countrySubdivisionType chosen
    Indicates the specific type or category of an administrative or territorial subdivision within a country (e.g., state, province, region).
  • 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_69a885fceb2c8190b47e0f7c0aefbff0 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a93aedd45c819085843ac843d640e8 completed March 5, 2026, 8:12 a.m.
PD Predicate disambiguation batch_69a907bdc19081908c84c5c0aa09e282 completed March 5, 2026, 4:34 a.m.
Created at: March 4, 2026, 7:27 p.m.