Triple

T12242571
Position Surface form Disambiguated ID Type / Status
Subject Rikugien Garden E291769 entity
Predicate city P40 FINISHED
Object Bunkyō E469604 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: Bunkyō | Statement: [Rikugien Garden, city, Bunkyō]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bunkyō
Context triple: [Rikugien Garden, city, Bunkyō]
  • A. Bunkyō chosen
    Bunkyō is a central Tokyo ward known for its universities, historic temples, and quiet residential neighborhoods.
  • B. Toshima
    Toshima is a special ward in northwest Tokyo known for the major commercial and entertainment hub of Ikebukuro and its dense urban residential districts.
  • C. Toshima
    Toshima is a small, sparsely populated volcanic island and village in Tokyo’s Izu Islands, known for its natural scenery and traditional rural lifestyle.
  • D. Kōtō
    Kōtō is a special ward in eastern Tokyo, Japan, known for its mix of residential neighborhoods, waterfront areas, and commercial districts.
  • E. Hamamatsuchō
    Hamamatsuchō is a business and transportation district in Tokyo known for its major train and monorail stations, office towers, and proximity to Tokyo Bay.
  • 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_69d6ab67950c8190be08450a06228c4b completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cb724448190be29fc1d2b946ab7 completed April 10, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff7559f0448190a992f0770ac8227a completed May 9, 2026, 5:56 p.m.
Created at: April 8, 2026, 9:51 p.m.