Triple

T17611882
Position Surface form Disambiguated ID Type / Status
Subject Suzuki Equator E428982 entity
Predicate manufacturer P490 FINISHED
Object Suzuki NE NERFINISHED

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: Suzuki | Statement: [Suzuki Equator, manufacturer, Suzuki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Suzuki
Context triple: [Suzuki Equator, manufacturer, Suzuki]
  • A. Suzuki
    Suzuki is a common Japanese surname borne by many notable individuals across sports, entertainment, and other fields.
  • B. Suzuki Motor Corporation chosen
    Suzuki Motor Corporation is a Japanese multinational automaker best known for its compact cars, motorcycles, and all-terrain vehicles sold worldwide.
  • C. Mugen-Honda
    Mugen-Honda was a racing engine partnership between Mugen Motorsports and Honda that supplied competitive Formula One power units in the 1990s.
  • D. Kawasaki
    Kawasaki is a major industrial and residential city in Kanagawa Prefecture, Japan, located between Tokyo and Yokohama along the Tama River.
  • E. Pak Suzuki Motor Company
    Pak Suzuki Motor Company is a leading Pakistani automobile manufacturer and assembler, primarily known for producing and selling affordable Suzuki-branded cars and motorcycles in the local market.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889e1c6148190ba76241e74688f8b completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46d2dfa688190a0b9b396bb6133cc completed April 19, 2026, 5:50 a.m.
Created at: April 10, 2026, 5:51 a.m.