Triple

T15278613
Position Surface form Disambiguated ID Type / Status
Subject Ginza Six E365206 entity
Predicate hasTenant P3277 FINISHED
Object Shiseido E835859 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: Shiseido | Statement: [Ginza Six, hasTenant, Shiseido]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shiseido
Context triple: [Ginza Six, hasTenant, Shiseido]
  • A. Shiseido chosen
    Shiseido is a major Japanese multinational cosmetics and skincare company known for its high-end beauty products and long-standing global presence.
  • B. L'Oréal
    L'Oréal is a French multinational cosmetics and beauty company recognized as one of the world’s largest and most influential personal care brands.
  • C. Lancôme
    Lancôme is a French luxury cosmetics and skincare brand renowned for its high-end perfumes, makeup, and beauty products.
  • D. Beauty Inc
    Beauty Inc is a beauty-focused media brand owned by Penske Media Corporation, covering trends, news, and analysis in the global cosmetics and personal care industry.
  • E. Biotherm
    Biotherm is a French skincare brand known for its use of aquatic ingredients and scientifically driven formulas for face and body care.
  • 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_69d85a103d9081908c1ea6c4c73ac8e3 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00953bc848190b83919f39d5ee37b completed April 15, 2026, 9:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69feef734f488190951d029183d456f5 completed May 9, 2026, 8:25 a.m.
Created at: April 10, 2026, 3:14 a.m.