Triple

T16858834
Position Surface form Disambiguated ID Type / Status
Subject Santiago–Rosalía de Castro Airport E409855 entity
Predicate servesAsHubFor P423 FINISHED
Object Ryanair E4144 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: Ryanair | Statement: [Santiago–Rosalía de Castro Airport, servesAsHubFor, Ryanair]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ryanair
Context triple: [Santiago–Rosalía de Castro Airport, servesAsHubFor, Ryanair]
  • A. Ryanair chosen
    Ryanair is a major Irish low-cost airline known for its extensive network of short-haul flights across Europe.
  • B. 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.
  • C. Flynas
    Flynas is a Saudi low-cost airline based in Riyadh that operates domestic and regional flights across the Middle East and beyond.
  • D. Aer Lingus
    Aer Lingus is the flag carrier airline of Ireland, operating international flights primarily between Ireland, Europe, and North America.
  • E. Flybe
    Flybe was a British regional airline that operated short-haul flights across the UK and Europe before ceasing operations.
  • 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_69d88395e6c88190b22730f335107c14 completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b501f72881909f7600311705fb33 completed April 18, 2026, 4:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00bb25300c8190a352037c21c244bd completed May 10, 2026, 5:06 p.m.
Created at: April 10, 2026, 5:24 a.m.