Triple

T13472013
Position Surface form Disambiguated ID Type / Status
Subject William Tennent Airport E311650 entity
Predicate hadControlTower P7890 FINISHED
Object no 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: no | Statement: [William Tennent Airport, hadControlTower, no]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hadControlTower
Context triple: [William Tennent Airport, hadControlTower, no]
  • A. hasControlTower chosen
    Indicates that one entity possesses, hosts, or is equipped with a control tower that manages or oversees its operations.
  • B. hasTower
    Indicates that one entity possesses, contains, or is characterized by the presence of a tower.
  • C. hasControlledAirspace
    Indicates that a specified location or region falls within airspace where aircraft operations are regulated and managed by an aviation authority.
  • D. hasRocketTower
    Indicates that an entity possesses or is equipped with a rocket-firing tower structure.
  • E. hasTowerPosition
    Indicates that an entity occupies or is assigned a specific position or location within a tower.
  • 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_69d806a938b8819097ec43a2229fc7f9 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaf22e5f88190b1078f006c8ef7c0 completed April 12, 2026, 2:41 p.m.
PD Predicate disambiguation batch_69dbadfddefc81909ef7fde23b181b5c completed April 12, 2026, 2:36 p.m.
Created at: April 9, 2026, 9:42 p.m.