Triple

T13469083
Position Surface form Disambiguated ID Type / Status
Subject Kashihara E311581 entity
Predicate hasMountain P10602 FINISHED
Object Mount Unebi E551238 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 Unebi | Statement: [Kashihara, hasMountain, Mount Unebi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mount Unebi
Context triple: [Kashihara, hasMountain, Mount Unebi]
  • A. Mount Unebi chosen
    Mount Unebi is a small, historically significant hill in Kashihara, Nara Prefecture, traditionally associated with Japan’s first emperor and early imperial mythology.
  • B. Mount Erice
    Mount Erice is a prominent mountain in western Sicily, Italy, known for its medieval hilltop town of Erice and panoramic views over the surrounding coast and islands.
  • C. Mount Usu
    Mount Usu is an active stratovolcano in Hokkaido, Japan, known for its frequent eruptions and dramatic impact on the surrounding landscape.
  • D. Mount Heha
    Mount Heha is the tallest mountain in Burundi, located in the Burundi Highlands near the city of Bujumbura.
  • E. Mount Haruna
    Mount Haruna is an active stratovolcano in Gunma Prefecture, Japan, known for its scenic caldera lake, hot springs, and popular hiking and sightseeing spots.
  • 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_69d806a938b8819097ec43a2229fc7f9 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaf21e46081908a00c9acf54f270f completed April 12, 2026, 2:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76ba344e0819098da09416a913851 completed May 3, 2026, 3:37 p.m.
Created at: April 9, 2026, 9:42 p.m.