Triple

T2251076
Position Surface form Disambiguated ID Type / Status
Subject Class C airspace E49616 entity
Predicate exampleAirportType P16113 FINISHED
Object airports with scheduled passenger service and significant operations 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: airports with scheduled passenger service and significant operations | Statement: [Class C airspace, exampleAirportType, airports with scheduled passenger service and significant operations]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: exampleAirportType
Context triple: [Class C airspace, exampleAirportType, airports with scheduled passenger service and significant operations]
  • A. hasAirfieldType
    Indicates that an airfield is classified as having a particular type or category of airfield.
  • B. associatedWithAirportType chosen
    Indicates that an entity has a connection or linkage to a specific category or type of airport.
  • C. isCivilAirport
    Indicates that an airport is designated and used primarily for civilian (non-military) aviation operations.
  • D. hubAirport
    Indicates that an airport serves as a primary hub or central operating base for a particular airline or carrier.
  • E. airportRole
    Indicates that an entity serves a specific functional role or capacity within the context of an airport.
  • 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_69a88aaa9250819095e127d0d77e8a32 completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc11d04688190abc04fac3a1804a9 completed March 7, 2026, 6:09 a.m.
PD Predicate disambiguation batch_69abbdb160248190aa75b38f11ad8602 completed March 7, 2026, 5:54 a.m.
Created at: March 4, 2026, 7:47 p.m.