Triple

T13860503
Position Surface form Disambiguated ID Type / Status
Subject Guy Kawasaki E333182 entity
Predicate familyName P18 FINISHED
Object Kawasaki E61828 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: [Guy Kawasaki, familyName, Kawasaki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kawasaki
Context triple: [Guy Kawasaki, familyName, Kawasaki]
  • A. Kawasaki chosen
    Kawasaki is a major industrial and residential city in Kanagawa Prefecture, Japan, located between Tokyo and Yokohama along the Tama River.
  • B. Kawasaki Daishi
    Kawasaki Daishi is a major Shingon Buddhist temple in Kawasaki, Japan, renowned as a popular site for New Year’s visits and prayers for protection from misfortune.
  • C. Suzuki
    Suzuki is a common Japanese surname borne by many notable individuals across sports, entertainment, and other fields.
  • D. Kawasaki Steel Mizushima
    Kawasaki Steel Mizushima was a Japanese company football club owned by Kawasaki Steel that later evolved into the professional J.League team Vissel Kobe.
  • E. Kawasaki Ninja series
    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.
  • 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_69d81c5ced9c8190b0e9bcc6effe5959 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02de38e48190b6ead95561031c32 completed April 14, 2026, 9:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c0fd3ffc8190965a730843411b80 completed May 3, 2026, 9:41 p.m.
Created at: April 9, 2026, 10:14 p.m.