Triple

T21184493
Position Surface form Disambiguated ID Type / Status
Subject Runway 04R/22L E522043 entity
Predicate isParallelTo P1868 FINISHED
Object Runway 04L/22R — NE NERFINISHED

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 04L/22R | Statement: [Runway 04R/22L, isParallelTo, Runway 04L/22R]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Runway 04L/22R
Context triple: [Runway 04R/22L, isParallelTo, Runway 04L/22R]
  • A. Runway 04L/22R chosen
    Runway 04L/22R is one of the primary paved runways used for aircraft takeoffs and landings at Wuhan Tianhe International Airport in Wuhan, China.
  • B. Runway 04L/22R
    Runway 04L/22R is one of the main parallel runways at Nice Côte d’Azur Airport, serving commercial air traffic on the French Riviera.
  • C. Runway 04L/22R
    Runway 04L/22R is one of the primary parallel runways at Chicago O'Hare International Airport, used for handling high volumes of commercial air traffic.
  • D. Runway 04L/22R
    Runway 04L/22R is one of the primary paved runways used for aircraft takeoffs and landings at Pisa International Airport in Italy.
  • E. Runway 04L/22R
    Runway 04L/22R is one of the primary paved runways used for aircraft takeoffs and landings at Sharm El Sheikh International Airport in Egypt.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b50ef1d48190b063aa342667df22 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e730205ce88190b0bb33003295d6e7 completed April 21, 2026, 8:06 a.m.
Created at: April 16, 2026, 3:06 p.m.