Triple

T806868
Position Surface form Disambiguated ID Type / Status
Subject Loganair E17455 entity
Predicate formerFranchisePartner P6217 FINISHED
Object Flybe
Flybe was a British regional airline that operated short-haul flights across the UK and Europe before ceasing operations.
 E106248 NE FINISHED

How this triple was built (4 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: Flybe | Statement: [Loganair, formerFranchisePartner, Flybe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Flybe
Context triple: [Loganair, formerFranchisePartner, Flybe]
  • A. Ryanair
    Ryanair is a major Irish low-cost airline known for its extensive network of short-haul flights across Europe.
  • B. 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.
  • C. Loganair
    Loganair is a Scottish regional airline that operates domestic and short-haul international flights across the United Kingdom and nearby destinations.
  • 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. easyJet
    easyJet is a major British low-cost airline operating extensive domestic and European routes.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Flybe
Triple: [Loganair, formerFranchisePartner, Flybe]
Generated description
Flybe was a British regional airline that operated short-haul flights across the UK and Europe before ceasing operations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Flybe
Target entity description: Flybe was a British regional airline that operated short-haul flights across the UK and Europe before ceasing operations.
  • A. Ryanair
    Ryanair is a major Irish low-cost airline known for its extensive network of short-haul flights across Europe.
  • B. 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.
  • C. Loganair
    Loganair is a Scottish regional airline that operates domestic and short-haul international flights across the United Kingdom and nearby destinations.
  • 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. easyJet
    easyJet is a major British low-cost airline operating extensive domestic and European routes.
  • F. None of above. chosen

Provenance (5 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_69a4937ae8a08190b5084a03d532b30e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4b2b503d48190bd4f33548a22d5fe completed March 1, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7c7103a00819087ad711a2ab99770 completed March 4, 2026, 5:45 a.m.
NEDg Description generation batch_69a7c7b8158c819095a82dcd02d6a7fb completed March 4, 2026, 5:48 a.m.
NED2 Entity disambiguation (via description) batch_69a7c888cd98819082dc39739d14dc67 completed March 4, 2026, 5:52 a.m.
Created at: March 1, 2026, 7:38 p.m.