Triple

T18151313
Position Surface form Disambiguated ID Type / Status
Subject Naoko Yamazaki E434508 entity
Predicate familyName P18 FINISHED
Object Yamazaki 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: Yamazaki | Statement: [Naoko Yamazaki, familyName, Yamazaki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yamazaki
Context triple: [Naoko Yamazaki, familyName, Yamazaki]
  • A. Yamazaki chosen
    Yamazaki is a common Japanese surname and place name associated with various individuals, companies, and locations in Japan.
  • B. Ozaki
    Ozaki is a Japanese surname borne by various notable figures in politics, literature, and the arts.
  • C. Yamakita
    Yamakita is a rural town in Kanagawa Prefecture, Japan, known for its mountainous terrain, hot springs, and access to outdoor activities such as hiking and river sports.
  • D. Oyamazaki
    Oyamazaki is a town in Kyoto Prefecture, Japan, known for its historical significance and scenic location at the confluence of major rivers and transportation routes.
  • E. Yamakoshi
    Yamakoshi is a recurring character from the Disney XD sitcom "Pair of Kings," known as a mystical fish with prophetic abilities and a quirky, comedic presence.
  • 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_69d8b90aac308190801e2c57d8c5bfe5 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4de38d4e08190bc4d430b70b7e288 completed April 19, 2026, 1:52 p.m.
Created at: April 10, 2026, 10:29 a.m.