Triple

T16026421
Position Surface form Disambiguated ID Type / Status
Subject Mazda3 E388728 entity
Predicate predecessor P97 FINISHED
Object Mazda 323 E1079452 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 323 | Statement: [Mazda3, predecessor, Mazda 323]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mazda 323
Context triple: [Mazda3, predecessor, Mazda 323]
  • A. Mazda 323 chosen
    The Mazda 323 is a compact car produced by Mazda that gained popularity worldwide for its practicality, reliability, and efficient performance across multiple generations.
  • B. Mazda 626
    The Mazda 626 is a mid-size family car produced by the Japanese automaker Mazda from the late 1970s to the early 2000s, known for its practicality, reliability, and global popularity.
  • C. Mazda SC
    Mazda SC was a Japanese company football club owned by Mazda that later evolved into the professional J.League team Sanfrecce Hiroshima.
  • D. Mazda Axela
    The Mazda Axela is the name used in Japan for the Mazda3, a popular compact car known for its sporty handling and stylish design.
  • E. Mazda3
    The Mazda3 is a popular compact car known for its sporty handling, stylish design, and well-appointed interior.
  • 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_69d86dada3808190825d5f80d72fbe88 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e18328707c8190b9a444c78faaaa04 completed April 17, 2026, 12:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffeb867ae88190945af88247d4c80b completed May 10, 2026, 2:20 a.m.
Created at: April 10, 2026, 4:56 a.m.