Triple

T10814311
Position Surface form Disambiguated ID Type / Status
Subject Omiya Bonsai Village E255184 entity
Predicate locatedIn P40 FINISHED
Object Omiya Ward E1016911 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: Omiya Ward | Statement: [Omiya Bonsai Village, locatedIn, Omiya Ward]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Omiya Ward
Context triple: [Omiya Bonsai Village, locatedIn, Omiya Ward]
  • A. Ōmiya-ku chosen
    Ōmiya-ku is a central ward of Saitama City in Japan, known as a major commercial and transportation hub in the Greater Tokyo area.
  • B. Toyohira Ward
    Toyohira Ward is one of the ten administrative wards of Sapporo, Japan, known for its residential neighborhoods, universities, and parks along the Toyohira River.
  • C. Suminoe Ward
    Suminoe Ward is one of Osaka City's 24 wards, known for its coastal location, residential districts, and industrial and port-related facilities.
  • D. Suginami Ward
    Suginami Ward is one of Tokyo’s 23 special wards, known as a largely residential area with numerous parks, local shopping streets, and a strong community atmosphere.
  • E. Arakawa Ward
    Arakawa Ward is a special ward in northeastern Tokyo, Japan, known for its mix of residential neighborhoods, traditional shitamachi atmosphere, and riverside areas.
  • 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_69d6aa8081448190a9324184f2bd1c26 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d733ece4488190b553a66c4b5188bc completed April 9, 2026, 5:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69f6d5e2b0408190866bbe9a3a56928b completed May 3, 2026, 4:58 a.m.
Created at: April 8, 2026, 9:18 p.m.