Triple

T1488682
Position Surface form Disambiguated ID Type / Status
Subject Tenerife South Airport E29526 entity
Predicate operator P179 FINISHED
Object Aena E140786 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: Aena | Statement: [Tenerife South Airport, operator, Aena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aena
Context triple: [Tenerife South Airport, operator, Aena]
  • A. Aena chosen
    Aena is the Spanish state-owned company that manages and operates the majority of airports in Spain and is one of the world’s largest airport operators by passenger traffic.
  • B. El Al
    El Al is Israel's flag carrier airline, known for its extensive international routes and stringent security measures.
  • C. Iberia Líneas Aéreas de España
    Iberia Líneas Aéreas de España is the flag carrier airline of Spain, operating an extensive network of domestic and international flights, primarily through its main hub in Madrid.
  • 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. Valencia Airport
    Valencia Airport is an international airport serving the city of Valencia and the surrounding region on Spain’s eastern Mediterranean coast.
  • 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_69a498da82e08190ba833330d05f380f completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c6a6095481909e9d406ac9a41828 completed March 1, 2026, 11:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad232f4b80819095a608816d4d2a34 completed March 8, 2026, 7:20 a.m.
Created at: March 1, 2026, 8:12 p.m.