Triple

T4203306
Position Surface form Disambiguated ID Type / Status
Subject Kagoshima Airport E86120 entity
Predicate locatedOnIsland P970 FINISHED
Object Kyushu E13149 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: Kyushu | Statement: [Kagoshima Airport, locatedOnIsland, Kyushu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kyushu
Context triple: [Kagoshima Airport, locatedOnIsland, Kyushu]
  • A. Kyushu chosen
    Kyushu is the southwesternmost of Japan’s main islands, known for its active volcanoes, hot springs, and historic cities such as Fukuoka and Nagasaki.
  • B. Shikoku
    Shikoku is the smallest of Japan’s four main islands, known for its mountainous landscapes, traditional rural culture, and the famous 88-temple Buddhist pilgrimage route.
  • C. Honshu
    Honshu is the largest and most populous island of Japan, home to major cities such as Tokyo, Osaka, and Kyoto.
  • D. Yamato region
    The Yamato region is the early political and cultural heartland of Japan, where the first unified Japanese state emerged under the Yamato court.
  • E. Setouchi
    Setouchi is a coastal town on Japan’s Amami Ōshima known for its subtropical climate, scenic bays, and traditional island culture.
  • 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_69af0380d470819091ffdb1161437266 completed March 9, 2026, 5:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfdeaa224c8190a115d8af390eea71 completed March 22, 2026, 12:20 p.m.
Created at: March 9, 2026, 3:49 p.m.