Triple

T13494448
Position Surface form Disambiguated ID Type / Status
Subject Naha urban area E320722 entity
Predicate hasAirport P105 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 urban area, hasAirport, Naha Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Naha Airport
Context triple: [Naha urban area, hasAirport, 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_69d807629d6c8190998f1b9bb12d2ed0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaf4da2c88190a867b53529d39545 completed April 12, 2026, 2:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75483a6f88190b3815fb8d97e65e4 completed May 3, 2026, 1:58 p.m.
Created at: April 9, 2026, 9:43 p.m.