Triple

T4039873
Position Surface form Disambiguated ID Type / Status
Subject Lyon–Saint-Exupéry Airport E83919 entity
Predicate focusCityFor P164 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: [Lyon–Saint-Exupéry Airport, focusCityFor, easyJet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: easyJet
Context triple: [Lyon–Saint-Exupéry Airport, focusCityFor, 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. TUI Airways
    TUI Airways is a British charter and scheduled airline that primarily serves leisure destinations across Europe and worldwide as part of the TUI Group.
  • 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_69aed92f7cf0819098e0539bdcc3767f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb39400881909d0f5430f04e441c completed March 9, 2026, 4:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b55649b75c819086b272f56ac73be4 completed March 14, 2026, 12:36 p.m.
Created at: March 9, 2026, 3:37 p.m.