Triple

T19783112
Position Surface form Disambiguated ID Type / Status
Subject Butuan City E475186 entity
Predicate hasAirport P105 FINISHED
Object Bancasi 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: Bancasi Airport | Statement: [Butuan City, hasAirport, Bancasi Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bancasi Airport
Context triple: [Butuan City, hasAirport, Bancasi Airport]
  • A. Bancasi Airport chosen
    Bancasi Airport is a domestic airport serving the city of Butuan in the Caraga region of Mindanao in the Philippines.
  • B. Ulei Airport
    Ulei Airport is a small regional airfield serving the island of Ambrym in Vanuatu, providing local and inter-island air connections.
  • C. Matei Airport
    Matei Airport is a small regional airport serving the island of Taveuni in Fiji, providing domestic connections and access for tourists to the island’s resorts and natural attractions.
  • D. Rinas Airport
    Rinas Airport is the main international airport serving Tirana and the primary air gateway to Albania.
  • E. Baljek Airport
    Baljek Airport is a small regional airport serving the town of Tura and the surrounding Garo Hills region in the Indian state of Meghalaya.
  • 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_69d8e51b014081908b263e167370529a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e653852e848190b8971981a164e8f9 completed April 20, 2026, 4:25 p.m.
Created at: April 10, 2026, 1:49 p.m.