Triple

T6715074
Position Surface form Disambiguated ID Type / Status
Subject Boulevard de la Croisette E153245 entity
Predicate followsCoastOf P1865 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: [Boulevard de la Croisette, followsCoastOf, Cannes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cannes
Context triple: [Boulevard de la Croisette, followsCoastOf, 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_69c68809b4608190a2509ddb5ab87f05 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d1246b748190aed94e8ab8625f7e completed March 27, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c70afa805c819098312fc0d06ec115 completed March 27, 2026, 10:55 p.m.
Created at: March 27, 2026, 2:07 p.m.