Triple

T19648636
Position Surface form Disambiguated ID Type / Status
Subject Hennadiy Zubko E471747 entity
Predicate governmentPositionType P9655 FINISHED
Object cabinet minister 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: cabinet minister | Statement: [Hennadiy Zubko, governmentPositionType, cabinet minister]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: governmentPositionType
Context triple: [Hennadiy Zubko, governmentPositionType, cabinet minister]
  • A. U.S.GovernmentPosition
    Indicates that an entity holds, held, or is associated with an official position or office within the United States government.
  • B. typeOfOffice
    Indicates the specific category or kind of office that an office entity belongs to (e.g., executive, legislative, judicial, or other office types).
  • C. governmentBodyType
    Indicates the classification or category of a governmental organization based on its structural or functional role.
  • D. governmentOfficeOrTitleOf chosen
    Indicates that one entity is a government office or official title held by, associated with, or designating the role of another entity.
  • E. governmentOffice
    Indicates that an entity functions as an official administrative or governmental office responsible for carrying out public or state-related duties.
  • 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_69d8e51395348190ac1416d46dfc6db0 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e64126cea88190a1a6929f46de4686 completed April 20, 2026, 3:07 p.m.
PD Predicate disambiguation batch_69e514e941008190898d978d7bde91e4 completed April 19, 2026, 5:46 p.m.
Created at: April 10, 2026, 1:44 p.m.