Triple

T4336574
Position Surface form Disambiguated ID Type / Status
Subject Kanto Mountains E97476 entity
Predicate hasPart P35 FINISHED
Object Mount Haruna E109169 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: Mount Haruna | Statement: [Kanto Mountains, hasPart, Mount Haruna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mount Haruna
Context triple: [Kanto Mountains, hasPart, Mount Haruna]
  • A. Mount Haruna chosen
    Mount Haruna is an active stratovolcano in Gunma Prefecture, Japan, known for its scenic caldera lake, hot springs, and popular hiking and sightseeing spots.
  • B. Mount Suiro
    Mount Suiro is the tallest mountain on Biliran Island in the Philippines, forming a prominent part of the island’s volcanic landscape.
  • C. Mount Asahi
    Mount Asahi is the highest peak in Japan’s Hokkaido region, known for its volcanic activity, alpine scenery, and popular hiking and skiing routes.
  • D. Mount Chōkai
    Mount Chōkai is a prominent stratovolcano on the border of Akita and Yamagata Prefectures in northern Japan, known for its symmetrical shape and scenic alpine landscapes.
  • E. Mount Tsurumi
    Mount Tsurumi is a volcanic mountain in Ōita Prefecture, Japan, known for its panoramic views, seasonal foliage, and ropeway access from the hot spring resort city of Beppu.
  • 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_69b3454662a481908fbcd0bbfaa3a0a4 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3516af43081908393fd0dad3d9382 completed March 12, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd569f30088190bdc9ea72fe35be35 completed March 20, 2026, 2:15 p.m.
Created at: March 12, 2026, 11:14 p.m.