Triple

T17627473
Position Surface form Disambiguated ID Type / Status
Subject Lötschberg railway line E429884 entity
Predicate passesThrough P225 FINISHED
Object Kandersteg 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: Kandersteg | Statement: [Lötschberg railway line, passesThrough, Kandersteg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kandersteg
Context triple: [Lötschberg railway line, passesThrough, Kandersteg]
  • A. Kandersteg chosen
    Kandersteg is a Swiss mountain village and popular tourist resort known for its scenic alpine landscapes, hiking trails, and access to Lake Oeschinen.
  • B. Wengen
    Wengen is a car-free Swiss alpine village and popular ski and hiking resort located in the Bernese Oberland region.
  • C. 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.
  • D. Klosters
    Klosters is a renowned Swiss Alpine village and ski resort in the canton of Graubünden, popular for its picturesque scenery and winter sports.
  • E. Weggis
    Weggis is a picturesque lakeside resort town in central Switzerland, known for its mild climate, scenic views of the Alps, and tourism on the shores of Lake Lucerne.
  • 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_69d889e37f308190a6aa0a69daff86c7 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46dbe3a308190a818d04f1a9b15f7 completed April 19, 2026, 5:53 a.m.
Created at: April 10, 2026, 5:52 a.m.