Triple

T15278609
Position Surface form Disambiguated ID Type / Status
Subject Ginza Six E365206 entity
Predicate hasTenant P3277 FINISHED
Object Céline E324687 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: Céline | Statement: [Ginza Six, hasTenant, Céline]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Céline
Context triple: [Ginza Six, hasTenant, Céline]
  • A. Céline
    Céline is the French given name of internationally renowned Canadian singer Céline Dion.
  • B. Celine chosen
    Celine is a French luxury fashion house known for its minimalist, modern designs in ready-to-wear, leather goods, and accessories.
  • C. Cécile
    Cécile is the sensitive and central protagonist of the French film "Cible émouvante," around whom the story’s emotional and narrative developments revolve.
  • D. La Malène
    La Malène is a small picturesque village in southern France, known as a gateway to the scenic Gorges du Tarn and popular for river-based outdoor activities.
  • E. Véronique
    Véronique is the idealistic young Maoist student protagonist in Jean-Luc Godard’s 1967 film "La Chinoise," whose political radicalization and intellectual debates drive the film’s exploration of revolutionary ideology.
  • 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.