Triple

T33652895
Position Surface form Disambiguated ID Type / Status
Subject SAS Connect E862145 entity
Predicate frequentFlyerProgramViaParent P13481 FINISHED
Object EuroBonus NE NERFINISHED

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: EuroBonus | Statement: [SAS Connect, frequentFlyerProgramViaParent, EuroBonus]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: frequentFlyerProgramViaParent
Context triple: [SAS Connect, frequentFlyerProgramViaParent, EuroBonus]
  • A. associatedWithFrequentFlyerProgram chosen
    Indicates that an entity has a connection or involvement with a frequent flyer program, such as membership, participation, or affiliation.
  • B. ownsAirline
    Indicates that one entity has legal ownership or controlling interest in an airline company.
  • C. airlineCustomer
    Indicates that one entity is a customer (passenger or client) of an airline entity, typically having purchased or used its air travel services.
  • D. hasParentProgram
    Indicates that a given program is hierarchically contained within or derived from another, higher-level program that serves as its parent.
  • E. frequentPartner
    Indicates that two entities regularly engage in a shared activity or interaction together more often than with others.
  • 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_69f349840ba881908e3bfce536aeb92b completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6fb19063c81909466b329655c8583 completed May 3, 2026, 7:36 a.m.
PD Predicate disambiguation batch_69f6f96badb08190994442c2aba840b1 completed May 3, 2026, 7:29 a.m.
Created at: May 1, 2026, 1:42 a.m.