Triple

T9724035
Position Surface form Disambiguated ID Type / Status
Subject Kiyosumi-Shirakawa E235555 entity
Predicate locatedIn P40 FINISHED
Object Kōtō E333569 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: Kōtō | Statement: [Kiyosumi-Shirakawa, locatedIn, Kōtō]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kōtō
Context triple: [Kiyosumi-Shirakawa, locatedIn, Kōtō]
  • A. Kōtō chosen
    Kōtō is a special ward in eastern Tokyo, Japan, known for its mix of residential neighborhoods, waterfront areas, and commercial districts.
  • 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. Bunkyō
    Bunkyō is a central Tokyo ward known for its universities, historic temples, and quiet residential neighborhoods.
  • D. Komagome
    Komagome is a residential and commercial neighborhood in Tokyo known for its traditional atmosphere, historic temples, and the renowned Rikugien Garden.
  • E. Kagurazaka
    Kagurazaka is a historic neighborhood in central Tokyo known for its narrow cobblestone streets, traditional ryotei restaurants, and blend of old geisha district charm with modern boutiques and cafes.
  • 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_69ca84d0123c819096f9dc3b6abb0881 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9e77096481908ffd315fecb1d5ec completed April 1, 2026, 10:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69dff74d59f88190bbd975521b16ae49 completed April 15, 2026, 8:38 p.m.
Created at: March 30, 2026, 8:21 p.m.