Triple

T5338285
Position Surface form Disambiguated ID Type / Status
Subject Salzburg Airport E123878 entity
Predicate hasRunway P105 FINISHED
Object Runway 15/33
Runway 15/33 is the principal paved runway at Salzburg Airport, used for handling both domestic and international air traffic.
 E614133 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 15/33 | Statement: [Salzburg Airport, hasRunway, Runway 15/33]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Runway 15/33
Context triple: [Salzburg Airport, hasRunway, Runway 15/33]
  • A. Runway 15/33
    Runway 15/33 is one of the primary runways at Ronald Reagan Washington National Airport in Arlington, Virginia, serving commercial air traffic for the Washington, D.C. area.
  • B. Runway 15/33
    Runway 15/33 is one of the primary paved runways at Martha's Vineyard Airport, used for handling regional and general aviation traffic.
  • C. Runway 15/33
    Runway 15/33 is one of the primary paved runways at Hamburg Airport, used for handling both domestic and international air traffic.
  • D. Runway 15/33
    Runway 15/33 is a primary paved runway used for aircraft operations at Maxwell Air Force Base in Alabama.
  • E. Runway 15/33
    Runway 15/33 is one of the primary paved runways used for aircraft takeoffs and landings at Kuala Lumpur International Airport in Malaysia.
  • 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 15/33
Triple: [Salzburg Airport, hasRunway, Runway 15/33]
Generated description
Runway 15/33 is the principal paved runway at Salzburg Airport, used for handling both domestic and international air traffic.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Runway 15/33
Target entity description: Runway 15/33 is the principal paved runway at Salzburg Airport, used for handling both domestic and international air traffic.
  • A. Runway 15/33
    Runway 15/33 is one of the primary paved runways at Hamburg Airport, used for handling both domestic and international air traffic.
  • B. Runway 15/33
    Runway 15/33 is one of the main paved runways at Helsinki Airport, used for both domestic and international air traffic operations.
  • C. Runway 15/33
    Runway 15/33 is one of the primary paved runways used for aircraft takeoffs and landings at Kuala Lumpur International Airport in Malaysia.
  • D. Runway 15/33
    Runway 15/33 is a primary paved runway at Charleston International Airport used for commercial and military aircraft operations.
  • E. Runway 15/33
    Runway 15/33 is the primary paved runway used for aircraft takeoffs and landings at Trollhättan–Vänersborg Airport in Sweden.
  • 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_69bd464b07f8819095aa76577c9829e4 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd85c6ec008190ad7a8a54360387d8 completed March 20, 2026, 5:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c70057abc48190a5855ce1c6029d81 completed March 27, 2026, 10:10 p.m.
NEDg Description generation batch_69c705b31bc8819087208b667104e363 completed March 27, 2026, 10:33 p.m.
NED2 Entity disambiguation (via description) batch_69c7065baaa08190b4046e0d372bf6f8 completed March 27, 2026, 10:36 p.m.
Created at: March 20, 2026, 2 p.m.