Triple

T16978666
Position Surface form Disambiguated ID Type / Status
Subject Tsukiji E411883 entity
Predicate near P350 FINISHED
Object Ginza 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: Ginza | Statement: [Tsukiji, near, Ginza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ginza
Context triple: [Tsukiji, near, Ginza]
  • A. Ginza
    "Ginza" is a reggaeton song by Colombian artist J Balvin that became a major Latin hit and helped solidify his international fame.
  • B. Ginza chosen
    Ginza is a famous upscale shopping, dining, and entertainment district in central Tokyo known for its luxury boutiques, department stores, and vibrant nightlife.
  • C. Otemachi
    Otemachi is a major business district in central Tokyo known for its concentration of corporate headquarters, financial institutions, and proximity to the Imperial Palace.
  • D. Ginza district
    The Ginza district is a famous upscale area in central Tokyo known for its luxury shopping, high-end dining, and vibrant nightlife.
  • E. Nagatacho
    Nagatacho is a central district in Tokyo, Japan, known as the political heart of the country and home to key government institutions such as the National Diet Building.
  • 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_69d886ca8f348190812768ea8d5055ce completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d185a9408190a991bf8a1ef694f0 completed April 18, 2026, 6:46 p.m.
Created at: April 10, 2026, 5:32 a.m.