Triple

T6409988
Position Surface form Disambiguated ID Type / Status
Subject Menorca Airport E127679 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: [Menorca Airport, operator, AENA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AENA
Context triple: [Menorca 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. Valencia Airport
    Valencia Airport is an international airport serving the city of Valencia and the surrounding region on Spain’s eastern Mediterranean coast.
  • C. Madrid–Torrejón Airport
    Madrid–Torrejón Airport is a joint civil-military airfield near Madrid, Spain, primarily used for military, governmental, and executive aviation rather than regular commercial passenger flights.
  • D. 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.
  • 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_69c0083723d88190b1e37b19df162c08 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c068cf81508190bc09e58ec45bc858 completed March 22, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c638b7582481909640965acf261dff completed March 27, 2026, 7:58 a.m.
Created at: March 22, 2026, 4:41 p.m.