Triple

T8393391
Position Surface form Disambiguated ID Type / Status
Subject Grand Forks International Airport E197995 entity
Predicate hasAirTrafficControl P7890 FINISHED
Object control tower 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: control tower | Statement: [Grand Forks International Airport, hasAirTrafficControl, control tower]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasAirTrafficControl
Context triple: [Grand Forks International Airport, hasAirTrafficControl, control tower]
  • A. hasControlTower chosen
    Indicates that one entity possesses, hosts, or is equipped with a control tower that manages or oversees its operations.
  • B. hasAirspace
    Indicates that one entity possesses, controls, or is associated with a defined region of airspace relative to another entity or area.
  • C. operationalControlOfFlights
    Indicates that one entity has the authority and responsibility to manage and direct the operation of specific flights conducted by another entity.
  • D. affectsAirTraffic
    Indicates that one entity causes changes or disruptions to the normal flow, safety, or management of air traffic.
  • E. appliesToAirspaceOf
    Indicates that a rule, restriction, or condition is specifically relevant to, or in effect within, a particular airspace.
  • 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_69ca82f816bc8190ab321c07d72208c1 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb8184788081909e9857afff629985 completed March 31, 2026, 8:10 a.m.
PD Predicate disambiguation batch_69cb70d24b248190a326aa6804f942b5 completed March 31, 2026, 6:59 a.m.
Created at: March 30, 2026, 6:03 p.m.