Triple

T3850546
Position Surface form Disambiguated ID Type / Status
Subject London Gatwick Airport E85283 entity
Predicate isBaseFor P2421 FINISHED
Object Wizz Air UK E95554 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: Wizz Air UK | Statement: [London Gatwick Airport, isBaseFor, Wizz Air UK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wizz Air UK
Context triple: [London Gatwick Airport, isBaseFor, Wizz Air UK]
  • A. Wizz Air chosen
    Wizz Air is a Hungarian ultra-low-cost airline known for operating an extensive network of budget flights across Europe and surrounding regions.
  • B. Ryanair
    Ryanair is a major Irish low-cost airline known for its extensive network of short-haul flights across Europe.
  • C. 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.
  • D. Flybe
    Flybe was a British regional airline that operated short-haul flights across the UK and Europe before ceasing operations.
  • E. Flynas
    Flynas is a Saudi low-cost airline based in Riyadh that operates domestic and regional flights across the Middle East 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_69aed936de1c81908f91bed80f70abb2 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeebcf67788190975105131baabc4b completed March 9, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5122eb2708190b1aa9da233481015 completed March 14, 2026, 7:45 a.m.
Created at: March 9, 2026, 3:19 p.m.