Triple

T4368011
Position Surface form Disambiguated ID Type / Status
Subject Gary/Chicago International Airport E98824 entity
Predicate hasAircraftMaintenanceServices P39380 FINISHED
Object yes LITERAL 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: yes | Statement: [Gary/Chicago International Airport, hasAircraftMaintenanceServices, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasAircraftMaintenanceServices
Context triple: [Gary/Chicago International Airport, hasAircraftMaintenanceServices, yes]
  • A. hasMaintenanceService
    Indicates that an entity receives or is covered by a maintenance service provided by another entity.
  • B. firstServiceAircraft
    Indicates that the subject aircraft is the first of its type to enter operational service with the specified operator or organization.
  • C. hasGroundHandlingServices
    Indicates that an entity provides or is associated with ground handling services for another entity, typically in an aviation or transportation context.
  • D. hasMaintenanceFacilities chosen
    Indicates that one entity provides or contains facilities where the other entity can be serviced, repaired, or maintained.
  • E. hasGeneralAviationFacilities
    Indicates that a location or airport provides facilities and services specifically for general aviation operations.
  • F. None of above.

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_69b3454db3708190aeafd814413c4c3d completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b352034d3881909ed4b2f9eef5e823 completed March 12, 2026, 11:53 p.m.
PD Predicate disambiguation batch_69b34f53e3cc8190bf5d4dbe2413bf65 completed March 12, 2026, 11:42 p.m.
Created at: March 12, 2026, 11:17 p.m.