Triple

T17848130
Position Surface form Disambiguated ID Type / Status
Subject Daikan-yama Station E445717 entity
Predicate servedArea P82 FINISHED
Object Daikanyama district 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: Daikanyama district | Statement: [Daikan-yama Station, servedArea, Daikanyama district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daikanyama district
Context triple: [Daikan-yama Station, servedArea, Daikanyama district]
  • A. Daikanyama district chosen
    Daikanyama district is a fashionable, upscale neighborhood in Tokyo known for its stylish boutiques, trendy cafés, and relaxed, residential atmosphere.
  • B. Aikawa district
    Aikawa district is a locality on Sado Island in Niigata Prefecture, Japan, historically known for its gold and silver mining operations.
  • C. Nezu district
    Nezu district is a historic neighborhood in Tokyo, Japan, known for its traditional atmosphere, old temples and shrines, and preserved shitamachi (downtown) charm.
  • D. Kitasaku District
    Kitasaku District is an administrative district in Nagano Prefecture, Japan, known for encompassing popular highland resort areas such as Karuizawa.
  • E. Arakawa district
    Arakawa district is a special ward in northeastern Tokyo known for its mix of traditional shitamachi neighborhoods, residential areas, and industrial zones.
  • 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_69d8b9f26f18819089c9e43250bee6ae completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48ffc5fec8190adc66f7b0e264d5f completed April 19, 2026, 8:19 a.m.
Created at: April 10, 2026, 10:16 a.m.