Triple

T6346320
Position Surface form Disambiguated ID Type / Status
Subject Lānaʻi Airport E142752 entity
Predicate cityServed P82 FINISHED
Object Lānaʻi City E26082 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: Lānaʻi City | Statement: [Lānaʻi Airport, cityServed, Lānaʻi City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lānaʻi City
Context triple: [Lānaʻi Airport, cityServed, Lānaʻi City]
  • A. Hāna
    Hāna is a small, remote town on the eastern coast of Maui, Hawaii, known for its lush landscapes, scenic coastal views, and the famously winding Road to Hāna.
  • B. Lānaʻi chosen
    Lānaʻi is one of the smaller inhabited Hawaiian Islands, known for its quiet, rural character and luxury resort tourism.
  • C. Wailea
    Wailea is a luxury resort community on the south shore of Maui, Hawaii, known for its upscale hotels, golf courses, and beautiful beaches.
  • D. Pāʻia
    Pāʻia is a small, laid-back town on Maui’s north shore in Hawaii, known for its surf culture, bohemian vibe, and proximity to popular windsurfing and kitesurfing beaches.
  • E. Wailuku
    Wailuku is a historic town on the Hawaiian island of Maui that serves as the county seat and a cultural and administrative center.
  • 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_69c008d5ab108190b346c465696824a9 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c067b907c4819085a3ea87589bc4be completed March 22, 2026, 10:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69c604454fd48190972476a0929dfb9d completed March 27, 2026, 4:15 a.m.
Created at: March 22, 2026, 4:31 p.m.