Triple

T11409573
Position Surface form Disambiguated ID Type / Status
Subject Edinburgh Airport E270332 entity
Predicate hasRunway P105 FINISHED
Object Runway 06/24
Runway 06/24 is a principal runway at Edinburgh Airport used for handling the airport’s commercial air traffic.
 E372217 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: Runway 06/24 | Statement: [Edinburgh Airport, hasRunway, Runway 06/24]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Runway 06/24
Context triple: [Edinburgh Airport, hasRunway, Runway 06/24]
  • A. Runway 06/24
    Runway 06/24 is one of the primary paved runways used for aircraft takeoffs and landings at Paris Orly Airport in France.
  • B. Runway 06/24
    Runway 06/24 is a principal runway at Istanbul’s Sabiha Gökçen International Airport, used for handling both domestic and international air traffic.
  • C. Runway 06/24
    Runway 06/24 is a primary paved runway at Lanseria International Airport in South Africa, aligned roughly northeast–southwest to accommodate prevailing winds and commercial traffic.
  • D. Runway 06/24
    Runway 06/24 is the primary paved runway at Lappeenranta Airport in Finland, used for both domestic and international air traffic operations.
  • E. Runway 06/24
    Runway 06/24 is a primary paved runway at Volgograd International Airport in Russia, used for handling the airport’s commercial air traffic.
  • 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: Runway 06/24
Triple: [Edinburgh Airport, hasRunway, Runway 06/24]
Generated description
Runway 06/24 is a principal runway at Edinburgh Airport used for handling the airport’s commercial air traffic.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Runway 06/24
Target entity description: Runway 06/24 is a principal runway at Edinburgh Airport used for handling the airport’s commercial air traffic.
  • A. Runway 06/24 chosen
    Runway 06/24 is a principal paved runway at Edinburgh Airport used for most commercial flight operations.
  • B. Runway 06/24
    Runway 06/24 is a principal paved runway at Shannon Airport in Ireland, used for handling commercial and other aircraft operations.
  • C. Runway 06/24
    Runway 06/24 is a principal runway at Istanbul’s Sabiha Gökçen International Airport, used for handling both domestic and international air traffic.
  • D. Runway 06/24
    Runway 06/24 is one of the primary paved runways used for aircraft takeoffs and landings at Paris Orly Airport in France.
  • E. Runway 06/24
    Runway 06/24 is a primary paved runway at San Bernardino International Airport in California, used for aircraft takeoffs and landings aligned roughly northeast–southwest.
  • F. None of above.

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_69d6aaddeaa8819088b30ef7b50598c9 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8014e72748190a01bde2f0105cedb completed April 9, 2026, 7:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f28076f52881908e4438f623af2749 completed April 29, 2026, 10:04 p.m.
NEDg Description generation batch_69f29147094481909b74e1f8187ee0cf completed April 29, 2026, 11:16 p.m.
NED2 Entity disambiguation (via description) batch_69f292a30e688190aa0c032bdd167eb0 completed April 29, 2026, 11:22 p.m.
Created at: April 8, 2026, 9:34 p.m.