Triple

T9524154
Position Surface form Disambiguated ID Type / Status
Subject Stelios Philanthropic Foundation E229717 entity
Predicate associatedWith P37 FINISHED
Object easyJet E6907 NE 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: easyJet | Statement: [Stelios Philanthropic Foundation, associatedWith, easyJet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: easyJet
Context triple: [Stelios Philanthropic Foundation, associatedWith, easyJet]
  • A. easyJet chosen
    easyJet is a major British low-cost airline operating extensive domestic and European routes.
  • B. Ryanair
    Ryanair is a major Irish low-cost airline known for its extensive network of short-haul flights across Europe.
  • C. Flybe
    Flybe was a British regional airline that operated short-haul flights across the UK and Europe before ceasing operations.
  • D. Wizz Air
    Wizz Air is a Hungarian ultra-low-cost airline known for operating an extensive network of budget flights across Europe and surrounding regions.
  • E. Jetairfly
    Jetairfly was the former brand name of TUI fly Belgium, a Belgian leisure airline operating charter and scheduled flights to holiday destinations across Europe and beyond.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69ca847870a881909d8d751a7d29da39 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9899f99481908d374528716027f8 completed April 1, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69d13a61fbd08190bb68ffe29da3a34a completed April 4, 2026, 4:20 p.m.
Created at: March 30, 2026, 7:59 p.m.