Triple

T2316251
Position Surface form Disambiguated ID Type / Status
Subject Mount Fuji E51069 entity
Predicate hasJapaneseName P9882 FINISHED
Object 富士山 E51069 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: 富士山 | Statement: [Mount Fuji, hasJapaneseName, 富士山]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 富士山
Context triple: [Mount Fuji, hasJapaneseName, 富士山]
  • A. Mount Fuji chosen
    Mount Fuji is Japan’s iconic, snow-capped stratovolcano and highest peak, renowned for its nearly symmetrical cone and cultural significance.
  • B. Mount Tai
    Mount Tai is one of China’s most famous and historically significant sacred mountains, revered in Chinese religion and culture for millennia.
  • C. Mount Hiei
    Mount Hiei is a historically significant mountain on the border of Kyoto and Shiga Prefectures in Japan, best known as the site of the Tendai Buddhist monastery Enryaku-ji and as a UNESCO World Heritage location.
  • D. Mount Rokko
    Mount Rokko is a prominent mountain range near Kobe, Japan, known for its panoramic night views, hiking trails, and recreational facilities.
  • E. Mount Hachiman
    Mount Hachiman is a scenic hill in Ōmihachiman, Shiga Prefecture, known for its historical significance, hiking trails, and panoramic views over the city and Lake Biwa.
  • 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_69a88b074b908190ae983dbca7757d88 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc61e72508190b335cda2c7fef130 completed March 7, 2026, 6:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae896236f08190b3874854279bbdf7 completed March 9, 2026, 8:48 a.m.
Created at: March 4, 2026, 7:49 p.m.