Triple

T4706614
Position Surface form Disambiguated ID Type / Status
Subject Trollhättan–Vänersborg Airport E104402 entity
Predicate hasRunway P105 FINISHED
Object Runway 15/33
Runway 15/33 is the primary paved runway used for aircraft takeoffs and landings at Trollhättan–Vänersborg Airport in Sweden.
 E566759 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: [Trollhättan–Vänersborg Airport, hasRunway, Runway 15/33]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Runway 15/33
Context triple: [Trollhättan–Vänersborg 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: [Trollhättan–Vänersborg Airport, hasRunway, Runway 15/33]
Generated description
Runway 15/33 is the primary paved runway used for aircraft takeoffs and landings at Trollhättan–Vänersborg Airport in Sweden.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Runway 15/33
Target entity description: Runway 15/33 is the primary paved runway used for aircraft takeoffs and landings at Trollhättan–Vänersborg Airport in Sweden.
  • A. 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.
  • B. 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.
  • C. Runway 15/33
    Runway 15/33 is one of the primary paved runways used for aircraft takeoffs and landings at Hollywood Burbank Airport in Burbank, California.
  • 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

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_69bd43eac3c08190af7e4020c6c3704c completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd63e9f0b88190820aa7fba2f91b6e completed March 20, 2026, 3:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69c11c83f8bc8190bdf139c9da2dd66b completed March 23, 2026, 10:57 a.m.
NEDg Description generation batch_69c11d9102648190a61e9a85ead0fff4 completed March 23, 2026, 11:01 a.m.
NED2 Entity disambiguation (via description) batch_69c11e76f5c48190adabb10472729cb2 completed March 23, 2026, 11:05 a.m.
Created at: March 20, 2026, 1:17 p.m.