Triple

T10015050
Position Surface form Disambiguated ID Type / Status
Subject Aichi Prefecture E199464 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object Okazaki E836252 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: Okazaki | Statement: [Aichi Prefecture, vehicleRegistrationCode, Okazaki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Okazaki
Context triple: [Aichi Prefecture, vehicleRegistrationCode, Okazaki]
  • A. Okazaki chosen
    Okazaki is a historic city in central Japan known as the birthplace of shogun Tokugawa Ieyasu and for its well-preserved castle and traditional festivals.
  • B. Ozaki
    Ozaki is a Japanese surname borne by various notable figures in politics, literature, and the arts.
  • C. Kawaguchi
    Kawaguchi is a major commuter city in the Greater Tokyo area of Japan, located just north of Tokyo in Saitama Prefecture.
  • D. Kodaira
    Kodaira is a suburban city in western Tokyo, Japan, known as a residential area with parks, schools, and convenient rail access to central Tokyo.
  • E. Nakanoshima
    Nakanoshima is a small Japanese island associated with Etajima in Hiroshima Prefecture, known for its coastal scenery and role within the local island group.
  • 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_69ca8315a1a08190ab310f25620f362b completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cdcd49b19c8190b429e3533d072648 completed April 2, 2026, 1:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2821b22488190913d743bc40a4c8e completed April 5, 2026, 3:39 p.m.
Created at: March 30, 2026, 8:52 p.m.