Triple

T28772465
Position Surface form Disambiguated ID Type / Status
Subject French state E726447 entity
Predicate delegatesTransportCompetencesTo P50302 FINISHED
Object French regions 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: French regions | Statement: [French state, delegatesTransportCompetencesTo, French regions]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: delegatesTransportCompetencesTo
Context triple: [French state, delegatesTransportCompetencesTo, French regions]
  • A. delegationCharacteristic
    Indicates that a specific quality, condition, or attribute is associated with the act or arrangement of delegating responsibilities or authority between entities.
  • B. delegates chosen
    Indicates that one entity assigns or entrusts a task, responsibility, or authority to another entity to act on its behalf.
  • C. tookOverCompetenceFrom
    Indicates that one entity assumed responsibility, authority, or functional control previously held by another entity.
  • D. entrustedTo
    Indicates that responsibility, care, or control of something has been formally given by one party to another.
  • E. canDelegateTo
    Indicates that one entity has the authority or ability to transfer or assign its responsibilities, tasks, or decision-making power to another entity.
  • 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_69f03199997c8190b6ae43fb19312443 completed April 28, 2026, 4:03 a.m.
NER Named-entity recognition batch_69f658ee40088190b71e1219407690d0 completed May 2, 2026, 8:05 p.m.
PD Predicate disambiguation batch_69f65760fd3081908ffe014a5e2bf069 completed May 2, 2026, 7:58 p.m.
Created at: April 28, 2026, 6:16 a.m.