Triple

T3067611
Position Surface form Disambiguated ID Type / Status
Subject HNM E62142 entity
Predicate locatedIn P40 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: [HNM, locatedIn, Hana Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hana Airport
Context triple: [HNM, locatedIn, 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. 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.
  • C. Kish International Airport
    Kish International Airport is the main air gateway serving Iran’s resort and free-trade zone of Kish Island in the Persian Gulf.
  • D. Senai International Airport
    Senai International Airport is a major airport in the Malaysian state of Johor that serves the city of Johor Bahru and the surrounding southern region as a key domestic and regional air travel hub.
  • E. Clow International Airport
    Clow International Airport is a public general aviation airport located in Bolingbrook, Illinois, primarily serving private and recreational pilots.
  • 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_69ad85793e5c8190a358049bc4a98d8c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada0fea06881909e5251eea26599ac completed March 8, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b373888b948190b84d7bfa908f15ad completed March 13, 2026, 2:16 a.m.
Created at: March 8, 2026, 3:02 p.m.