Triple

T4259529
Position Surface form Disambiguated ID Type / Status
Subject Montgomery Regional Airport E96068 entity
Predicate hasCommercialAirlines P35742 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: [Montgomery Regional Airport, hasCommercialAirlines, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCommercialAirlines
Context triple: [Montgomery Regional Airport, hasCommercialAirlines, yes]
  • A. hasAirlines chosen
    Indicates that one entity (such as an airport, city, or country) is served by or associated with one or more airline operators.
  • B. airlinesUse
    Indicates that certain airlines operate, employ, or make use of a specified resource, service, or system.
  • C. operatesFlightsInRegion
    Indicates that an airline or carrier runs or provides flight services within a specified geographic region.
  • D. hasRegionalAirport
    Indicates that a place or region possesses or is served by a regional airport.
  • E. hasDomesticFlights
    Indicates that an airline or airport operates flights within the same country, connecting domestic destinations.
  • 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_69b3454095ac81909c2494f7ff294af1 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34f7fe7348190baed8d214268b756 completed March 12, 2026, 11:42 p.m.
PD Predicate disambiguation batch_69b347f73e008190a908a48ef389945a completed March 12, 2026, 11:10 p.m.
Created at: March 12, 2026, 11:06 p.m.