Triple

T6281290
Position Surface form Disambiguated ID Type / Status
Subject Aena E140786 entity
Predicate operates P24 FINISHED
Object Almería Airport E335399 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: Almería Airport | Statement: [Aena, operates, Almería Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Almería Airport
Context triple: [Aena, operates, Almería Airport]
  • A. Almería Airport chosen
    Almería Airport is a regional international airport in southeastern Spain that serves the city of Almería and the surrounding Costa de Almería tourist area.
  • B. Málaga Airport
    Málaga Airport is a major international airport in southern Spain serving the Costa del Sol and the city of Málaga as one of the country’s busiest tourist gateways.
  • C. Murcia–San Javier Airport
    Murcia–San Javier Airport is a Spanish airport in the Region of Murcia that serves both civilian flights and military aviation activities.
  • D. Alicante–Elche Airport
    Alicante–Elche Airport is a major international airport in Spain’s Valencian Community serving the Costa Blanca region and the cities of Alicante and Elche.
  • E. Jerez Airport
    Jerez Airport is a regional international airport in southern Spain serving the city of Jerez de la Frontera and the wider Cádiz province, handling both commercial flights and seasonal tourist traffic.
  • 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_69c6d50184a081908286d92166fd1c00 completed March 27, 2026, 7:05 p.m.
Created at: March 22, 2026, 4:26 p.m.