Triple

T1360996
Position Surface form Disambiguated ID Type / Status
Subject Buk District E29097 entity
Predicate subdivisionType2 P3599 FINISHED
Object Provincial level 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: Provincial level | Statement: [Buk District, subdivisionType2, Provincial level]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: subdivisionType2
Context triple: [Buk District, subdivisionType2, Provincial level]
  • A. subdivisionRank chosen
    Indicates the hierarchical level or type of administrative or territorial subdivision that an entity occupies within a larger organizational or geographic structure.
  • B. subdivisionName1
    Indicates that the first named subdivision is identified by a specific name or designation within a larger geographic or organizational hierarchy.
  • C. hasSubdivision
    Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
  • D. hasSubdivisionCode
    Indicates that an entity is associated with a specific code identifying one of its internal subdivisions (such as a state, province, or region).
  • E. isResidentialSuburbOf
    Indicates that one area is a residential suburb that is part of or lies within the urban region of another area.
  • 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_69a498d77abc8190913bf57e5f51d2c4 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c2b156b081909c99ada70a969fc0 completed March 1, 2026, 10:50 p.m.
PD Predicate disambiguation batch_69a4bef945c08190a027472fdd695ea5 completed March 1, 2026, 10:34 p.m.
Created at: March 1, 2026, 7:56 p.m.