Triple

T7416330
Position Surface form Disambiguated ID Type / Status
Subject Kutani ware E171138 entity
Predicate hasProductionCenter P70121 FINISHED
Object Komatsu E551408 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: Komatsu | Statement: [Kutani ware, hasProductionCenter, Komatsu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Komatsu
Context triple: [Kutani ware, hasProductionCenter, Komatsu]
  • A. Komatsu chosen
    Komatsu is a city in Ishikawa Prefecture, Japan, known for its manufacturing industry and as the namesake of the global construction equipment company Komatsu Ltd.
  • B. Kamiyama
    Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
  • C. Takamado
    Takamado is a Japanese imperial family name most prominently associated with the late Prince Takamado and his descendants, a branch of Japan’s royal household.
  • D. Takaishi
    Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
  • E. Oyamazaki
    Oyamazaki is a town in Kyoto Prefecture, Japan, known for its historical significance and scenic location at the confluence of major rivers and transportation routes.
  • 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_69c68a618bdc81908d8018edadecd1a4 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f4ec85488190a1f7fb913e0fbe35 completed March 27, 2026, 9:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c94db29c248190acf3349adc82656c completed March 29, 2026, 4:05 p.m.
Created at: March 27, 2026, 3:11 p.m.