Triple

T33159550
Position Surface form Disambiguated ID Type / Status
Subject Paul Gorguloff E848686 entity
Predicate victimHeldOffice P176402 FINISHED
Object President of France 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 France | Statement: [Paul Gorguloff, victimHeldOffice, President of France]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: victimHeldOffice
Context triple: [Paul Gorguloff, victimHeldOffice, President of France]
  • A. possibleOfficeHeld
    Indicates that an entity may have held, or is a candidate to have held, a particular office or position, without asserting it as a confirmed fact.
  • B. housedOfficeHolder
    Indicates that a particular location or building served as the place where a specific office holder was based or accommodated in their official capacity.
  • C. electoralOfficeHolder
    Indicates that one entity holds or occupies a particular elected office or position in a political or electoral system.
  • D. builtUnderPoliticalOffice
    Indicates that the construction or creation of something occurred during the tenure of a particular political office or officeholder.
  • E. heldPoliticalOfficeIn
    Indicates that an entity served in a political office or position within a specified governmental body or jurisdiction.
  • F. None of above. chosen

Provenance (4 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_69f3495b02d08190bb3d366823dffc21 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6e02ba6b881908dfafc52d3b75f1c completed May 3, 2026, 5:42 a.m.
PD Predicate disambiguation batch_69f6de09c2f481909f8b2545d3208c9f completed May 3, 2026, 5:32 a.m.
PDg Predicate description generation batch_69f6e029f0f88190b1f88d82a4a2cabd completed May 3, 2026, 5:42 a.m.
Created at: May 1, 2026, 1:28 a.m.