Triple

T1768558
Position Surface form Disambiguated ID Type / Status
Subject Marie-Thérèse Walter E38819 entity
Predicate placeOfDeath P21 FINISHED
Object Antibes E65894 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: Antibes | Statement: [Marie-Thérèse Walter, placeOfDeath, Antibes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Antibes
Context triple: [Marie-Thérèse Walter, placeOfDeath, Antibes]
  • A. Antibes chosen
    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.
  • B. Le Cannet
    Le Cannet is a commune in the Alpes-Maritimes department of southeastern France, located just north of Cannes on the French Riviera.
  • C. Saint-Tropez
    Saint-Tropez is a coastal town on the French Riviera, famed as a glamorous Mediterranean resort and former artists’ haven.
  • D. 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.
  • E. Juan-les-Pins
    Juan-les-Pins is a seaside resort town on the French Riviera, known for its beaches, nightlife, and jazz festival.
  • 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_69a8862e61708190af97b9838cc3f5de completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa648d9f2c8190aca4884648a69eb0 completed March 6, 2026, 5:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae5d7d1f6c8190a1033c784091ffb8 completed March 9, 2026, 5:41 a.m.
Created at: March 4, 2026, 7:31 p.m.