Triple

T17826804
Position Surface form Disambiguated ID Type / Status
Subject Collombey-Muraz E445138 entity
Predicate borders P224 FINISHED
Object Aigle NE NERFINISHED

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: Aigle | Statement: [Collombey-Muraz, borders, Aigle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aigle
Context triple: [Collombey-Muraz, borders, Aigle]
  • A. Aigle chosen
    Aigle is a historic town in southwestern Switzerland known for its medieval castle and surrounding vineyards in the canton of Vaud.
  • B. L’Aigle
    L’Aigle is a small historic town in northwestern France known for its role in the Orne department and its traditional Norman character.
  • C. Aigle Azur
    Aigle Azur was a French airline known for operating scheduled passenger services, particularly linking France with North and West African destinations.
  • D. Nid d'Aigle
    Nid d'Aigle is a high-altitude railway terminus and popular starting point for mountaineers heading towards Mont Blanc in the French Alps.
  • E. Loiseau
    Loiseau is a French surname most notably borne by Gustave Loiseau, a post-Impressionist painter known for his landscapes and depictions of rural France.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f0de78819099395b14db75a8a6 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48914e20481908883d1da194f446c completed April 19, 2026, 7:49 a.m.
Created at: April 10, 2026, 10:15 a.m.