Triple

T4920601
Position Surface form Disambiguated ID Type / Status
Subject Joey Dunlop E110454 entity
Predicate team P3756 FINISHED
Object Kawasaki E391118 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: Kawasaki | Statement: [Joey Dunlop, team, Kawasaki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kawasaki
Context triple: [Joey Dunlop, team, Kawasaki]
  • A. Kawasaki
    Kawasaki is a major industrial and residential city in Kanagawa Prefecture, Japan, located between Tokyo and Yokohama along the Tama River.
  • B. Suzuki
    Suzuki is a common Japanese surname borne by many notable individuals across sports, entertainment, and other fields.
  • C. Kawasaki Ninja series chosen
    The Kawasaki Ninja series is a renowned line of high-performance sport motorcycles known for their aggressive styling, powerful engines, and strong presence in both street riding and motorcycle racing.
  • D. Suzuki Motor Corporation
    Suzuki Motor Corporation is a Japanese multinational automaker best known for its compact cars, motorcycles, and all-terrain vehicles sold worldwide.
  • E. Yamaha Motor Company
    Yamaha Motor Company is a Japanese manufacturer best known for its motorcycles, marine products, and power equipment, and is one of the world’s leading powersports brands.
  • 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_69bd4413f9908190afcff44d7929cc4c completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6ffabccc81909115ece1b04e2061 completed March 20, 2026, 4:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69be77a41ca08190a8fbfa405b15d68c completed March 21, 2026, 10:49 a.m.
Created at: March 20, 2026, 1:30 p.m.