Triple

T903342
Position Surface form Disambiguated ID Type / Status
Subject Sluha Narodu E19493 entity
Predicate holdsOffice P16080 FINISHED
Object President of Ukraine (through Volodymyr Zelenskyy) 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: President of Ukraine (through Volodymyr Zelenskyy) | Statement: [Sluha Narodu, holdsOffice, President of Ukraine (through Volodymyr Zelenskyy)]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: holdsOffice
Context triple: [Sluha Narodu, holdsOffice, President of Ukraine (through Volodymyr Zelenskyy)]
  • A. memberHoldsOffice chosen
    Indicates that a member occupies or serves in a specific official position or office within an organization or governing body.
  • B. alsoHoldsOfficeOf
    Indicates that an entity currently holding one office or position simultaneously holds another office or position as well.
  • C. officeHolderOf
    Indicates that a person holds or has held an official position or role within a specified organization, institution, or office.
  • D. servesAsOfficeOf
    Indicates that one entity functions as the official office, headquarters, or administrative base for another entity.
  • E. typeOfOffice
    Indicates the specific category or kind of office that an office entity belongs to (e.g., executive, legislative, judicial, or other office types).
  • 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_69a4939e889c8190ac148b3ac1a7f90b completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ad58334881908df191140b786780 completed March 1, 2026, 9:19 p.m.
PD Predicate disambiguation batch_69a4aa98caec8190bbcc38320090f058 completed March 1, 2026, 9:07 p.m.
Created at: March 1, 2026, 7:39 p.m.