Triple

T17515615
Position Surface form Disambiguated ID Type / Status
Subject Zugerberg E426559 entity
Predicate nearbyCity P350 FINISHED
Object Zug 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: Zug | Statement: [Zugerberg, nearbyCity, Zug]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zug
Context triple: [Zugerberg, nearbyCity, Zug]
  • A. Zug chosen
    Zug is a small, affluent Swiss city and canton known for its low taxes, picturesque lakeside setting, and role as a hub for international businesses and cryptocurrency companies.
  • B. Türnich
    Türnich is a district of the town of Kerpen in North Rhine-Westphalia, Germany, known as a residential area within the Cologne metropolitan region.
  • C. Olten
    Olten is a town in the canton of Solothurn in northwestern Switzerland, known as an important railway junction and regional economic center.
  • D. Kloten
    Kloten is a town in the canton of Zurich in northern Switzerland, best known as the home of Zurich Airport.
  • E. Bülach
    Bülach is a town in northern Switzerland that serves as a regional center near Zurich, known for its residential character and proximity to Zurich Airport.
  • 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_69d889dd9164819087b1dc3c9240c870 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4526097388190ba1a949064962a24 completed April 19, 2026, 3:56 a.m.
Created at: April 10, 2026, 5:49 a.m.