Triple

T21163557
Position Surface form Disambiguated ID Type / Status
Subject Shannon, Ireland E521499 entity
Predicate hasNearbyAirportFunction P92912 FINISHED
Object international air travel hub 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: international air travel hub | Statement: [Shannon, Ireland, hasNearbyAirportFunction, international air travel hub]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasNearbyAirportFunction
Context triple: [Shannon, Ireland, hasNearbyAirportFunction, international air travel hub]
  • A. nearbyAirportAccess chosen
    Indicates that an entity has convenient access to an airport located within a short distance or travel time.
  • B. nearbyAirportRelationship
    Indicates that one location has an airport situated close enough to serve it conveniently, establishing a nearby-airport relationship between the two.
  • C. nearestAirport
    Indicates that one airport is the closest in distance to a given location or entity compared to all other airports.
  • D. hasNearbyGeneralAviationAirport
    Indicates that an entity is located close to a general aviation airport, such that the airport can reasonably serve it for non-commercial or private air traffic.
  • E. nearestLargerAirport
    Indicates that one airport is the closest geographically among all airports that are larger (e.g., by traffic or capacity) than a given reference 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_69e0b50d1ea481909c07e63c3ead9316 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e72533fe88819082e14d71c36140be completed April 21, 2026, 7:20 a.m.
PD Predicate disambiguation batch_69e5f5f8a5bc819081918c7fa8e4496d completed April 20, 2026, 9:46 a.m.
Created at: April 16, 2026, 2:59 p.m.