Triple

T6281299
Position Surface form Disambiguated ID Type / Status
Subject Aena E140786 entity
Predicate operates P24 FINISHED
Object San Sebastián Airport E576423 NE 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: San Sebastián Airport | Statement: [Aena, operates, San Sebastián Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Sebastián Airport
Context triple: [Aena, operates, San Sebastián Airport]
  • A. San Sebastián Airport chosen
    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.
  • B. 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.
  • C. Bilbao Airport
    Bilbao Airport is a major international airport in northern Spain serving the city of Bilbao and the Basque Country region.
  • D. 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.
  • E. Asturias Airport
    Asturias Airport is a regional international airport in northern Spain serving the Asturias region with domestic and limited international flights.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69c008cd17c8819082b82d3fbeb68047 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063dee62881908347283f16dcbe68 completed March 22, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c71a5979208190b3bedb6234181245 completed March 28, 2026, 12:01 a.m.
Created at: March 22, 2026, 4:26 p.m.