Triple

T668100
Position Surface form Disambiguated ID Type / Status
Subject Grand Prix (Cannes Film Festival) E12909 entity
Predicate awardedIn P2207 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: [Grand Prix (Cannes Film Festival), awardedIn, Cannes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cannes
Context triple: [Grand Prix (Cannes Film Festival), awardedIn, 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. 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.
  • D. Marseille
    Marseille is a historic Mediterranean port city in southern France known for its diverse culture, maritime heritage, and role as a major economic hub.
  • E. Évian-les-Bains
    Évian-les-Bains is a French spa and resort town in the Alps renowned worldwide for its mineral water and scenic lakeside setting.
  • 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_69a493355dec819098d4244b2fa34885 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49ff921288190a2e5edb201ba69ee completed March 1, 2026, 8:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69a64a4f8f0081909686a76b4fddda60 completed March 3, 2026, 2:41 a.m.
Created at: March 1, 2026, 7:36 p.m.