Triple

T11623701
Position Surface form Disambiguated ID Type / Status
Subject Bursa Province E276205 entity
Predicate hasUNSubdivisionCode P22016 FINISHED
Object TR-16 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: TR-16 | Statement: [Bursa Province, hasUNSubdivisionCode, TR-16]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasUNSubdivisionCode
Context triple: [Bursa Province, hasUNSubdivisionCode, TR-16]
  • A. hasSubdivisionCode chosen
    Indicates that an entity is associated with a specific code identifying one of its internal subdivisions (such as a state, province, or region).
  • B. hasSubdivisionCodePart
    Indicates that an entity’s subdivision code includes or is composed of the referenced code segment or component.
  • C. hasSubdivision
    Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
  • D. hasHigherLevelSubdivision
    Indicates that one administrative or organizational unit is contained within and subordinate to a larger, higher-level subdivision.
  • E. hasNationalSubdivisionType
    Indicates that an entity is associated with a specific type or category of national-level administrative subdivision (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_69d6aafa51148190ab84940694c00235 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a122a3708190ab6513dad4c4fde7 completed April 10, 2026, 7:05 a.m.
PD Predicate disambiguation batch_69d85dd6503c819081f9045e9d5c4f3f completed April 10, 2026, 2:17 a.m.
Created at: April 8, 2026, 9:39 p.m.