Triple

T1086602
Position Surface form Disambiguated ID Type / Status
Subject Rancho-Boyeros Airport E24065 entity
Predicate locatedIn P40 FINISHED
Object Boyeros E27782 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: Boyeros | Statement: [Rancho-Boyeros Airport, locatedIn, Boyeros]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Boyeros
Context triple: [Rancho-Boyeros Airport, locatedIn, Boyeros]
  • A. Boyeros chosen
    Boyeros is a municipality in Havana, Cuba, known for hosting the country’s main international gateway, José Martí International Airport.
  • B. Azaña
    Azaña is the surname of Manuel Azaña, a prominent Spanish politician and writer who served as President of the Second Spanish Republic.
  • C. Rivas
    Rivas is a city in southwestern Nicaragua known as a regional commercial center and gateway between Lake Nicaragua and the Pacific coast.
  • D. Ibora
    Ibora was an ancient town in Pontus (in modern-day Turkey) known as the birthplace of the influential Christian monk and theologian Evagrius Ponticus.
  • E. Pérez-Castejón
    Pérez-Castejón is the compound surname of Spanish politician Pedro Sánchez, reflecting his paternal and maternal family lineages.
  • 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_69a49404428c819092dcc9632f5f7b8b completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4b963161081908a523c8d63871652 completed March 1, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac5ea491ec8190bf6bd84ecb5af341 completed March 7, 2026, 5:21 p.m.
Created at: March 1, 2026, 7:42 p.m.