Triple

T13026110
Position Surface form Disambiguated ID Type / Status
Subject Glacier de Leschaux E326310 entity
Predicate department P1467 FINISHED
Object Haute-Savoie E16739 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: Haute-Savoie | Statement: [Glacier de Leschaux, department, Haute-Savoie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haute-Savoie
Context triple: [Glacier de Leschaux, department, Haute-Savoie]
  • A. Haute-Savoie chosen
    Haute-Savoie is a department in the Auvergne-Rhône-Alpes region of southeastern France, renowned for its Alpine landscapes, ski resorts, and proximity to Mont Blanc and the Swiss and Italian borders.
  • B. Savoie
    Savoie is a mountainous department in southeastern France, known for its Alpine landscapes, ski resorts, and rich Savoyard cultural heritage.
  • C. Hautes-Alpes
    Hautes-Alpes is a mountainous department in southeastern France known for its Alpine landscapes, ski resorts, and outdoor recreation.
  • D. Montgenèvre
    Montgenèvre is a French Alpine ski resort village in the Hautes-Alpes department, known for its high-altitude slopes and location near the Italian border.
  • E. Gros-de-Vaud
    Gros-de-Vaud is a predominantly rural district in the canton of Vaud, Switzerland, known for its agricultural landscape and small towns.
  • 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_69d8076cc45c81908123123f43e69266 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97efac71881908a21d70c3c6ce099 completed April 10, 2026, 10:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbcb86148190ad1b19c6e8764397 completed May 3, 2026, 4:15 a.m.
Created at: April 9, 2026, 8:53 p.m.