Triple

T2316254
Position Surface form Disambiguated ID Type / Status
Subject Mount Fuji E51069 entity
Predicate nearCity P350 FINISHED
Object Fujiyoshida E77310 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: Fujiyoshida | Statement: [Mount Fuji, nearCity, Fujiyoshida]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fujiyoshida
Context triple: [Mount Fuji, nearCity, Fujiyoshida]
  • A. Fujiyoshida chosen
    Fujiyoshida is a Japanese city in Yamanashi Prefecture, best known as a gateway to Mount Fuji and a popular base for climbers and tourists visiting the iconic volcano.
  • B. Fujiidera
    Fujiidera is a city in Osaka Prefecture, Japan, known for its historical temples and role as a residential and commercial suburb in the Kansai region.
  • C. Marunouchi
    Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
  • D. Suzuya
    Suzuya is a Japanese Mogami-class heavy cruiser of the Imperial Japanese Navy that served during World War II.
  • E. Aoyama
    Aoyama is an upscale district in Tokyo known for its high-end fashion boutiques, modern architecture, and trendy cafes and galleries.
  • 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_69b4fad35a0c8190a07cc7877fbfec04 completed March 14, 2026, 6:06 a.m.
Created at: March 4, 2026, 7:49 p.m.