Triple

T23242597
Position Surface form Disambiguated ID Type / Status
Subject Loiu E581497 entity
Predicate hasAirport P105 FINISHED
Object Bilbao Airport NE NERFINISHED

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: Bilbao Airport | Statement: [Loiu, hasAirport, Bilbao Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bilbao Airport
Context triple: [Loiu, hasAirport, Bilbao Airport]
  • A. Bilbao Airport chosen
    Bilbao Airport is a major international airport in northern Spain serving the city of Bilbao and the Basque Country region.
  • B. Pamplona Airport
    Pamplona Airport is a regional Spanish airport serving the city of Pamplona and the surrounding Navarre region with domestic and limited international flights.
  • C. Zaragoza Airport
    Zaragoza Airport is an international airport in northeastern Spain that serves the city of Zaragoza and functions as both a civilian and important military and cargo hub.
  • D. San Sebastián Airport
    San Sebastián Airport is a small regional airport in Spain’s Basque Country that serves the city of Donostia-San Sebastián and its surrounding area.
  • E. Burgos Airport
    Burgos Airport is a regional public airport in Burgos, Spain, providing domestic air services and connecting the city to the national air transport network.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e2460556f88190be1744a84a84173f completed April 17, 2026, 2:39 p.m.
NER Named-entity recognition batch_69f192ef109881908c8fba7316c90910 completed April 29, 2026, 5:11 a.m.
Created at: April 17, 2026, 4:10 p.m.