Triple

T8698095
Position Surface form Disambiguated ID Type / Status
Subject 3.0 L Duratec V6 E206451 entity
Predicate usedInBrand P12411 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: [3.0 L Duratec V6, usedInBrand, Mazda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mazda
Context triple: [3.0 L Duratec V6, usedInBrand, 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_69ca83555b6c8190abe930dd397e863b completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc58af50408190a3b81100a759795e completed March 31, 2026, 11:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69cef40e7a2881909e2d7eee0d931992 completed April 2, 2026, 10:56 p.m.
Created at: March 30, 2026, 6:34 p.m.