Triple

T4098469
Position Surface form Disambiguated ID Type / Status
Subject Helsinki Airport E87879 entity
Predicate hasRunway P105 FINISHED
Object 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.
 E525930 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: [Helsinki Airport, hasRunway, Runway 15/33]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Runway 15/33
Context triple: [Helsinki 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: [Helsinki Airport, hasRunway, Runway 15/33]
Generated description
Runway 15/33 is one of the main paved runways at Helsinki Airport, used for both domestic and international air traffic operations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Runway 15/33
Target entity description: Runway 15/33 is one of the main paved runways at Helsinki Airport, used for both domestic and international air traffic operations.
  • 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 primary paved runways used for aircraft takeoffs and landings at Kuala Lumpur International Airport in Malaysia.
  • C. Runway 15/33
    Runway 15/33 is one of the designated landing and takeoff runways at Chicago O'Hare International Airport, supporting its role as a major global aviation hub.
  • D. 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.
  • E. Runway 15/33
    Runway 15/33 is a primary paved runway used for aircraft operations at Maxwell Air Force Base in Alabama.
  • 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_69aed94564cc8190a9c1457daedb6e7f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefce017708190a4d33753fd32a7bb completed March 9, 2026, 5:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfa1b5c0e081909c9a923eef50018c completed March 22, 2026, 8 a.m.
NEDg Description generation batch_69bfa27d71fc8190aee4de452eb259fe completed March 22, 2026, 8:04 a.m.
NED2 Entity disambiguation (via description) batch_69bfa30af20c8190a759a3b7b108371b completed March 22, 2026, 8:06 a.m.
Created at: March 9, 2026, 3:40 p.m.