Triple

T2480083
Position Surface form Disambiguated ID Type / Status
Subject Japanese National Railways E55792 entity
Predicate operatedRegion P6665 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: [Japanese National Railways, operatedRegion, Kyushu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kyushu
Context triple: [Japanese National Railways, operatedRegion, 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. Setouchi
    Setouchi is a coastal town on Japan’s Amami Ōshima known for its subtropical climate, scenic bays, and traditional island culture.
  • E. San’in region
    The San’in region is a coastal area along the Sea of Japan in western Honshu, known for its rural landscapes, historic towns, and relatively cooler, cloudier climate compared to other parts of Japan.
  • 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_69ab49e670a88190b928e08302381710 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd160a9708190b28d2f5538ea129a completed March 7, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69bd6f6fe04c8190bffabb9225ef6c2a completed March 20, 2026, 4:01 p.m.
Created at: March 6, 2026, 9:45 p.m.