Triple

T4046263
Position Surface form Disambiguated ID Type / Status
Subject Fukuoka Airport E84073 entity
Predicate locatedIn P40 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: [Fukuoka Airport, locatedIn, Kyushu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kyushu
Context triple: [Fukuoka Airport, locatedIn, 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_69aed930bd5c819083e7dcc14fc44f69 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb6135b481909d2be890a2140ff9 completed March 9, 2026, 4:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69be77765a788190aaf4637ad4cab5ed completed March 21, 2026, 10:48 a.m.
Created at: March 9, 2026, 3:37 p.m.