Triple

T4984475
Position Surface form Disambiguated ID Type / Status
Subject Hiroshima Toyo Carp E111966 entity
Predicate owner P347 FINISHED
Object Mazda E91822 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: Mazda | Statement: [Hiroshima Toyo Carp, owner, Mazda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mazda
Context triple: [Hiroshima Toyo Carp, owner, Mazda]
  • A. Mazda Motor Corporation chosen
    Mazda Motor Corporation is a Japanese automaker known for its innovative engineering, including rotary engines and driver-focused vehicles, and for its global presence in the automotive market.
  • B. Mazda Motor Manufacturing USA
    Mazda Motor Manufacturing USA was a former automotive manufacturing joint venture facility in Flat Rock, Michigan, that produced vehicles for Mazda (and later Ford) before being renamed the Flat Rock Assembly Plant.
  • C. Honda
    Honda is a historic Colombian river port city on the Magdalena River, known for its colonial architecture and numerous bridges.
  • D. Honda
    Honda is a major Japanese automobile and motorcycle manufacturer known for its reliable, fuel-efficient vehicles and global market presence.
  • E. Mitsubishi
    Mitsubishi is a major Japanese multinational conglomerate known for its diverse businesses in industries such as automotive, heavy industry, finance, and electronics.
  • 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_69bd441adc208190b70a033a0741d01e completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd7255d7b4819098b537df5b1a4c3c completed March 20, 2026, 4:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69be8a1891c48190b85bec5e97f75e44 completed March 21, 2026, 12:07 p.m.
Created at: March 20, 2026, 1:33 p.m.