Triple

T4415184
Position Surface form Disambiguated ID Type / Status
Subject KMVY E94951 entity
Predicate hasRunway P105 FINISHED
Object Runway 15/33 E105309 NE FINISHED

How this triple was built (2 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: [KMVY, hasRunway, Runway 15/33]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Runway 15/33
Context triple: [KMVY, 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 chosen
    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.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69b34539638c8190abfea3eb29425210 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b354eabb2481908ad10d21e1379e7f completed March 13, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69bff2a7e5b081909d3d64fc62c48eb3 completed March 22, 2026, 1:46 p.m.
Created at: March 12, 2026, 11:29 p.m.