Triple

T12397882
Position Surface form Disambiguated ID Type / Status
Subject Out of Competition E296165 entity
Predicate location P40 FINISHED
Object Cannes, France 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, France | Statement: [Out of Competition, location, Cannes, France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cannes, France
Context triple: [Out of Competition, location, Cannes, France]
  • 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. AS Cannes
    AS Cannes is a French professional football club known for developing notable players such as Patrick Vieira and Zinedine Zidane.
  • 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. Saint-Tropez
    Saint-Tropez is a coastal town on the French Riviera, famed as a glamorous Mediterranean resort and former artists’ haven.
  • E. Saint-Jean-Cap-Ferrat, France
    Saint-Jean-Cap-Ferrat, France is an exclusive Mediterranean seaside commune on the French Riviera known for its luxurious villas, scenic peninsula, and affluent residents.
  • 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_69d6ad9f464c81909db36d7e96e34b9e completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d93fd448f08190af425a569d7ed158 completed April 10, 2026, 6:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63480a8bc8190885130f63a3ec761 completed May 2, 2026, 5:29 p.m.
Created at: April 8, 2026, 9:54 p.m.