Triple

T11388153
Position Surface form Disambiguated ID Type / Status
Subject John Sutton E269760 entity
Predicate placeOfDeath P21 FINISHED
Object Alpes-Maritimes E73900 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: Alpes-Maritimes | Statement: [John Sutton, placeOfDeath, Alpes-Maritimes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alpes-Maritimes
Context triple: [John Sutton, placeOfDeath, Alpes-Maritimes]
  • A. Alpes-Maritimes chosen
    Alpes-Maritimes is a department in southeastern France on the Mediterranean coast, known for the French Riviera cities of Nice and Cannes and its mix of coastal and Alpine landscapes.
  • B. Bouches-du-Rhône
    Bouches-du-Rhône is a department in southern France known for the city of Marseille, its Mediterranean coastline, and parts of the historic Provence region.
  • C. Hautes-Alpes
    Hautes-Alpes is a mountainous department in southeastern France known for its Alpine landscapes, ski resorts, and outdoor recreation.
  • D. Drôme
    Drôme is a department in southeastern France known for its diverse landscapes, historic towns, and location between the Alps and the Rhône Valley.
  • E. Alpes-de-Haute-Provence
    Alpes-de-Haute-Provence is a mountainous department in southeastern France known for its Alpine landscapes, lavender fields, and picturesque Provençal villages.
  • 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_69d6aacdbc6c8190af6dc3d5f5d22836 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7fc389d4c81909515a5c8b0099c36 completed April 9, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5b813cfc48190a10d9b78953112ae completed April 20, 2026, 5:22 a.m.
Created at: April 8, 2026, 9:34 p.m.