Triple

T764768
Position Surface form Disambiguated ID Type / Status
Subject Pierre Bonnard E16149 entity
Predicate workLocation P7 FINISHED
Object Le Cannet E183830 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: Le Cannet | Statement: [Pierre Bonnard, workLocation, Le Cannet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Le Cannet
Context triple: [Pierre Bonnard, workLocation, Le Cannet]
  • A. Le Cannet chosen
    Le Cannet is a commune in the Alpes-Maritimes department of southeastern France, located just north of Cannes on the French Riviera.
  • B. 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.
  • C. Leucate
    Leucate is a coastal commune in southern France known for its Mediterranean beaches, wind sports, and scenic limestone cliffs.
  • D. Saint-Tropez
    Saint-Tropez is a coastal town on the French Riviera, famed as a glamorous Mediterranean resort and former artists’ haven.
  • E. Aix-en-Provence
    Aix-en-Provence is a historic and picturesque city in southern France, renowned for its Provençal charm, fountains, and as the hometown of painter Paul Cézanne.
  • 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_69a493684ee48190bd43b7c78da4aec8 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a69dfeb08190b54a476cfa66e6d6 completed March 1, 2026, 8:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad606f1c008190adca6fa6f0d6cd66 completed March 8, 2026, 11:41 a.m.
Created at: March 1, 2026, 7:37 p.m.