Triple

T19340583
Position Surface form Disambiguated ID Type / Status
Subject Zweisimmen E483743 entity
Predicate connectedTo P37 FINISHED
Object Gstaad 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: Gstaad | Statement: [Zweisimmen, connectedTo, Gstaad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gstaad
Context triple: [Zweisimmen, connectedTo, Gstaad]
  • A. Gstaad chosen
    Gstaad is an upscale Swiss alpine resort village renowned for its luxury hotels, skiing, and exclusive social scene.
  • B. St. Moritz
    St. Moritz is a famous Swiss alpine resort town renowned for its luxury tourism, winter sports, and role as a two-time Winter Olympics host.
  • C. Zermatt
    Zermatt is a renowned Swiss alpine resort village in the canton of Valais, famous for its skiing, mountaineering, and proximity to iconic peaks like the Matterhorn.
  • D. Visp
    Visp is a small town in the canton of Valais in southwestern Switzerland, situated in the Rhône valley and known as a regional transport hub and gateway to nearby Alpine resorts.
  • E. Arosa
    Arosa is a Swiss alpine resort town in the canton of Graubünden, known for its skiing, hiking, and scenic mountain landscapes.
  • 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_69d8e8d244f8819080eb1f3491300db2 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e61856c0948190a3166b3bf3810e43 completed April 20, 2026, 12:13 p.m.
Created at: April 10, 2026, 1:33 p.m.