Triple

T16207124
Position Surface form Disambiguated ID Type / Status
Subject Naha Airport Station E393355 entity
Predicate locatedIn P40 FINISHED
Object Naha Airport E90732 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: Naha Airport | Statement: [Naha Airport Station, locatedIn, Naha Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Naha Airport
Context triple: [Naha Airport Station, locatedIn, Naha Airport]
  • A. Naha Airport chosen
    Naha Airport is the main commercial airport serving Okinawa Prefecture in Japan, acting as a key domestic and regional hub in the Ryukyu Islands.
  • B. Hana Airport
    Hana Airport is a small regional airport serving the remote town of Hāna on the eastern coast of Maui, Hawaii.
  • C. Momote Airport
    Momote Airport is a regional airport serving Manus Province in Papua New Guinea, providing vital air connectivity for passengers and cargo to this remote island area.
  • D. Kirakira Airport
    Kirakira Airport is a small regional airfield serving the town of Kirakira and surrounding communities in Makira-Ulawa Province of the Solomon Islands.
  • E. Yoron Airport
    Yoron Airport is a small regional airport on Yoron Island in Kagoshima Prefecture, Japan, providing domestic air links to the mainland and nearby islands.
  • 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_69d87f1f5bd08190bd01cac0d5b9d2ef completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e227101a3c819095ef40e50bf66433 completed April 17, 2026, 12:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a002d9c35248190a5540a692503c989 completed May 10, 2026, 7:02 a.m.
Created at: April 10, 2026, 5:03 a.m.