Triple

T8960981
Position Surface form Disambiguated ID Type / Status
Subject Hāna E214001 entity
Predicate hasAirport P105 FINISHED
Object Hana Airport E62141 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: Hana Airport | Statement: [Hāna, hasAirport, Hana Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hana Airport
Context triple: [Hāna, hasAirport, Hana Airport]
  • A. Hana Airport chosen
    Hana Airport is a small regional airport serving the remote town of Hāna on the eastern coast of Maui, Hawaii.
  • B. 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.
  • C. 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.
  • D. Tajima Airport
    Tajima Airport is a regional airport in northern Hyogo Prefecture, Japan, primarily serving domestic flights and connecting the Tajima area with major Japanese cities.
  • E. Sado Airport
    Sado Airport is a regional airport serving Sado Island in Niigata Prefecture, Japan, providing domestic air connections to the mainland.
  • 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_69ca839cd6008190a1546a701a56710c completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6748baa88190ac54e701dc4d6212 completed April 1, 2026, 12:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2281e332c819093444685d37b9251 completed April 5, 2026, 9:15 a.m.
Created at: March 30, 2026, 7 p.m.