Triple

T16412040
Position Surface form Disambiguated ID Type / Status
Subject Portes du Soleil E398589 entity
Predicate hasResort P4287 FINISHED
Object Abondance E912632 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: Abondance | Statement: [Portes du Soleil, hasResort, Abondance]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Abondance
Context triple: [Portes du Soleil, hasResort, Abondance]
  • A. Abondance
    Abondance is a Cubist painting by French artist Henri Le Fauconnier, recognized for its bold geometric forms and vibrant, fragmented depiction of figures and space.
  • B. Abondance chosen
    Abondance is a traditional alpine village in the French Haute-Savoie region, renowned for its namesake cheese and picturesque mountain setting.
  • C. Ornières
    Ornières is one of the prose-poems in Arthur Rimbaud’s influential collection Les Illuminations, noted for its vivid, experimental imagery.
  • D. Auregnais
    Auregnais is an extinct Norman dialect once spoken on the Channel Island of Alderney.
  • E. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • 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_69d87f2950248190bc8ad9b9bebdc8c8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32874a0cc8190874aea10b1d13004 completed April 18, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a003c68b7408190a9612a57f146dc30 completed May 10, 2026, 8:06 a.m.
Created at: April 10, 2026, 5:09 a.m.