Triple

T91498
Position Surface form Disambiguated ID Type / Status
Subject Terminal 5 E1837 entity
Predicate hasAirlineTenant P3277 FINISHED
Object Aer Lingus
Aer Lingus is the flag carrier airline of Ireland, operating international flights primarily between Ireland, Europe, and North America.
 E24183 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: Aer Lingus | Statement: [Terminal 5, hasAirlineTenant, Aer Lingus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Aer Lingus
Context triple: [Terminal 5, hasAirlineTenant, Aer Lingus]
  • 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. Virgin Atlantic
    Virgin Atlantic is a British long-haul airline known for its transatlantic flights, distinctive branding, and innovative in-flight services.
  • D. Loganair
    Loganair is a Scottish regional airline that operates domestic and short-haul international flights across the United Kingdom and nearby destinations.
  • E. Transavia France
    Transavia France is a French low-cost airline and subsidiary of the Air France-KLM group, operating primarily short- and medium-haul leisure routes across Europe and the Mediterranean.
  • 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: Aer Lingus
Triple: [Terminal 5, hasAirlineTenant, Aer Lingus]
Generated description
Aer Lingus is the flag carrier airline of Ireland, operating international flights primarily between Ireland, Europe, and North America.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Aer Lingus
Target entity description: Aer Lingus is the flag carrier airline of Ireland, operating international flights primarily between Ireland, Europe, and North America.
  • 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. Virgin Atlantic
    Virgin Atlantic is a British long-haul airline known for its transatlantic flights, distinctive branding, and innovative in-flight services.
  • D. Loganair
    Loganair is a Scottish regional airline that operates domestic and short-haul international flights across the United Kingdom and nearby destinations.
  • E. Transavia France
    Transavia France is a French low-cost airline and subsidiary of the Air France-KLM group, operating primarily short- and medium-haul leisure routes across Europe and the Mediterranean.
  • 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_69a24d1a97dc819094e6c021fe9b05a7 completed Feb. 28, 2026, 2:04 a.m.
NER Named-entity recognition batch_69a2567dd770819088eb77ffc6d2d1cf completed Feb. 28, 2026, 2:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69a305dff8b88190b82db3adf474b271 completed Feb. 28, 2026, 3:12 p.m.
NEDg Description generation batch_69a309bbb7108190af09feaddee9d00c completed Feb. 28, 2026, 3:28 p.m.
NED2 Entity disambiguation (via description) batch_69a30a1b9240819088e762ff13df4c32 completed Feb. 28, 2026, 3:30 p.m.
Created at: Feb. 28, 2026, 2:07 a.m.