Triple

T3812296
Position Surface form Disambiguated ID Type / Status
Subject City of Beverly Hills E93163 entity
Predicate hasSisterCity P919 FINISHED
Object Cannes E47528 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: Cannes | Statement: [City of Beverly Hills, hasSisterCity, Cannes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cannes
Context triple: [City of Beverly Hills, hasSisterCity, Cannes]
  • A. Cannes chosen
    Cannes is a glamorous resort city on the French Riviera, internationally renowned for its luxury tourism, beaches, and role as a global center of the film industry.
  • B. Saint-Tropez
    Saint-Tropez is a coastal town on the French Riviera, famed as a glamorous Mediterranean resort and former artists’ haven.
  • C. Sophia Antipolis
    Sophia Antipolis is a major technology and research park in southeastern France, known as a European hub for telecommunications, information technology, and innovation.
  • D. Grasse
    Grasse is a town in southeastern France renowned as the world’s perfume capital and a historic center of the fragrance industry.
  • E. Antibes
    Antibes is a historic resort town on the French Riviera known for its Mediterranean coastline, old town, and association with artists such as Pablo Picasso.
  • 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_69aed96a60088190ab1df8390fffc935 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aee8db8a288190afd1e3b9dcf02e97 completed March 9, 2026, 3:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69b503f3590c8190b18e2e9dfd84cbcd completed March 14, 2026, 6:45 a.m.
Created at: March 9, 2026, 3:16 p.m.