Triple

T9982457
Position Surface form Disambiguated ID Type / Status
Subject Volkswagen Jetta E196485 entity
Predicate competitor P1375 FINISHED
Object Mazda3 E388728 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: Mazda3 | Statement: [Volkswagen Jetta, competitor, Mazda3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mazda3
Context triple: [Volkswagen Jetta, competitor, Mazda3]
  • A. Mazda3 chosen
    The Mazda3 is a popular compact car known for its sporty handling, stylish design, and well-appointed interior.
  • B. Mazda6
    The Mazda6 is a mid-size family sedan known for its sporty handling, stylish design, and strong value in the mainstream car market.
  • C. Mazda2
    The Mazda2 is a subcompact car known for its agile handling, fuel efficiency, and stylish design, positioned as an affordable entry-level model in Mazda’s lineup.
  • D. Mazda CX-5
    The Mazda CX-5 is a compact crossover SUV known for its stylish design, engaging driving dynamics, and efficient Skyactiv technology.
  • E. Mazda Tribute
    The Mazda Tribute is a compact crossover SUV produced in the early 2000s through a collaboration between Mazda and Ford, sharing its platform with the Ford Escape and Mercury Mariner.
  • 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_69ca82efbce081908179b4b9c65096eb completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb8bca41081909c04fb77603403b9 completed April 2, 2026, 12:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69d257e888908190a7187e26ba025a44 completed April 5, 2026, 12:39 p.m.
Created at: March 30, 2026, 8:49 p.m.