Triple

T13510317
Position Surface form Disambiguated ID Type / Status
Subject Mount Ōminakami E321121 entity
Predicate near P350 FINISHED
Object Minakami NE NERFINISHED

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: Minakami | Statement: [Mount Ōminakami, near, Minakami]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Minakami
Context triple: [Mount Ōminakami, near, Minakami]
  • A. Minakami chosen
    Minakami is a mountainous town in Gunma Prefecture, Japan, known for its hot springs, outdoor sports, and scenic natural landscapes.
  • B. Minamitane
    Minamitane is a town on Tanegashima Island in Kagoshima Prefecture, Japan, known for hosting Japan’s main spaceport facilities nearby.
  • C. Kamiyama
    Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
  • D. Minokamo
    Minokamo is a city in Gifu Prefecture, Japan, known as a regional hub that blends industrial activity with agricultural areas along the Kiso River.
  • E. Minamiizu
    Minamiizu is a coastal town at the southern tip of Japan’s Izu Peninsula, known for its scenic beaches, hot springs, and rugged seaside landscapes.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d807629d6c8190998f1b9bb12d2ed0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaf86a6208190be8c18f7a0158f23 completed April 12, 2026, 2:43 p.m.
Created at: April 9, 2026, 9:43 p.m.