Triple

T16442988
Position Surface form Disambiguated ID Type / Status
Subject Riederfurka E399350 entity
Predicate accessFrom P1985 FINISHED
Object Mörel E393390 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: Mörel | Statement: [Riederfurka, accessFrom, Mörel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mörel
Context triple: [Riederfurka, accessFrom, Mörel]
  • A. Mörel chosen
    Mörel is a Swiss village in the canton of Valais that serves as a gateway to the Aletsch Arena in the Alps.
  • B. Mouriès
    Mouriès is a village in southern France’s Provence region, known for its olive oil production and location near the Alpilles hills.
  • C. Maurepas
    Maurepas is a commune in the Yvelines department in the Île-de-France region of north-central France, known as a residential suburb southwest of Paris.
  • D. Arenenberg
    Arenenberg is a historic estate on the shores of Lake Constance in Switzerland, best known as the residence and later death place of Queen Hortense de Beauharnais and a key site of Napoleonic-era history.
  • E. Vaugier
    Vaugier is the surname of Emmanuelle Vaugier, a Canadian actress and model known for roles in television series such as "Two and a Half Men" and "Smallville."
  • 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_69d87f2c6778819080fcfae53be8f12a completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32cd8d2988190acb5722a15623319 completed April 18, 2026, 7:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00458f8f3c8190ad5eff2ad2a32dea completed May 10, 2026, 8:45 a.m.
Created at: April 10, 2026, 5:10 a.m.