Triple

T3887273
Position Surface form Disambiguated ID Type / Status
Subject TOM E92972 entity
Predicate identifies P310 FINISHED
Object TUI Airways E16522 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: TUI Airways | Statement: [TOM, identifies, TUI Airways]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TUI Airways
Context triple: [TOM, identifies, TUI Airways]
  • A. TUI Airways chosen
    TUI Airways is a British charter and scheduled airline that primarily serves leisure destinations across Europe and worldwide as part of the TUI Group.
  • B. Virgin Atlantic
    Virgin Atlantic is a British long-haul airline known for its transatlantic flights, distinctive branding, and innovative in-flight services.
  • C. British Airways
    British Airways is the United Kingdom’s flag carrier airline and one of Europe’s largest international airlines, operating an extensive global network from its main hub at London Heathrow Airport.
  • D. Flybe
    Flybe was a British regional airline that operated short-haul flights across the UK and Europe before ceasing operations.
  • E. Britannia Airways
    Britannia Airways was a major British charter airline that operated holiday flights across Europe and beyond before being rebranded under the Thomson name.
  • 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_69aed9697de0819087c2559295ff3d12 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeecabe3548190a5cbf9d0af0bcfb6 completed March 9, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b54c3151e8819082d72756875a9b1d completed March 14, 2026, 11:53 a.m.
Created at: March 9, 2026, 3:20 p.m.