Triple

T4203293
Position Surface form Disambiguated ID Type / Status
Subject Kagoshima Airport E86120 entity
Predicate connectsToIsland P27557 FINISHED
Object Yakushima E444729 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: Yakushima | Statement: [Kagoshima Airport, connectsToIsland, Yakushima]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yakushima
Context triple: [Kagoshima Airport, connectsToIsland, Yakushima]
  • A. Yakushima chosen
    Yakushima is a subtropical Japanese island renowned for its ancient cedar forests, rich biodiversity, and status as a UNESCO World Heritage Site.
  • B. Yashima
    Yashima is a historic plateau and former island in Takamatsu, Kagawa Prefecture, known for its panoramic views of the Seto Inland Sea and as a key battlefield of the Genpei War.
  • C. Tokunoshima
    Tokunoshima is a subtropical Japanese island in Kagoshima Prefecture known for its unique biodiversity, traditional culture, and role as part of the Amami archipelago.
  • D. Kikaijima
    Kikaijima is a small coral island in Japan’s Kagoshima Prefecture, known for its limestone plateau landscape, sugarcane cultivation, and location within the Amami archipelago.
  • E. Rokkō Island
    Rokkō Island is a large man-made island in Kobe, Japan, known for its residential areas, commercial facilities, and port-related infrastructure in Osaka Bay.
  • 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_69aed93b89f48190a31f6d57c760e42f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0b2db368819080c1d652b4acfd0c completed March 9, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf7fbd0bc881908ba07edb75479b97 completed March 22, 2026, 5:35 a.m.
Created at: March 9, 2026, 3:49 p.m.