Triple

T18241896
Position Surface form Disambiguated ID Type / Status
Subject Vila do Corvo E436835 entity
Predicate hasAirport P105 FINISHED
Object Corvo Airport NE NERFINISHED

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: Corvo Airport | Statement: [Vila do Corvo, hasAirport, Corvo Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Corvo Airport
Context triple: [Vila do Corvo, hasAirport, Corvo Airport]
  • A. Corvo Airport chosen
    Corvo Airport is a small regional airport serving the remote island of Corvo in Portugal’s Azores archipelago.
  • B. El Lencero Airport
    El Lencero Airport is a small regional airport serving the city of Xalapa and the surrounding area in the state of Veracruz, Mexico.
  • C. Leonora Airport
    Leonora Airport is a regional airfield in Leonora, Western Australia, serving the town and surrounding mining areas with passenger and charter flights.
  • D. Es Sénia Airport
    Es Sénia Airport is the former name of the international airport serving Oran, Algeria, now known as Oran Ahmed Ben Bella Airport.
  • E. Frans Sales Lega Airport
    Frans Sales Lega Airport is a regional airport serving the town of Ruteng on the island of Flores in East Nusa Tenggara, Indonesia.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b91104e08190a8241f7d260a5162 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4f7e387f481909d72574fb7d17923 completed April 19, 2026, 3:42 p.m.
Created at: April 10, 2026, 10:33 a.m.