Triple

T17877993
Position Surface form Disambiguated ID Type / Status
Subject Bishop International Airport E447006 entity
Predicate airportClassification P424 FINISHED
Object primary commercial service airport 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: primary commercial service airport | Statement: [Bishop International Airport, airportClassification, primary commercial service airport]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: airportClassification
Context triple: [Bishop International Airport, airportClassification, primary commercial service airport]
  • A. hasAirportClassification chosen
    Indicates that an airport is assigned a specific classification or category based on defined criteria.
  • B. airportDesignation
    Indicates that an entity is officially designated or classified as an airport.
  • C. ICAOClassificationSystem
    Indicates a relationship where an entity is categorized or defined according to the standards and categories of the ICAO (International Civil Aviation Organization) classification system.
  • D. airportSpecialization
    Indicates that an airport is specialized or designated for a particular primary function, service type, or category of operations.
  • E. isCivilAirport
    Indicates that an airport is designated and used primarily for civilian (non-military) 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_69d8b9f4c22c819093c2680434472894 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49c0c46108190b8edef2572b5ba90 completed April 19, 2026, 9:10 a.m.
PD Predicate disambiguation batch_69e3d8e6d2e88190ad9ef9f8a99f13e6 completed April 18, 2026, 7:17 p.m.
Created at: April 10, 2026, 10:18 a.m.