Triple

T17115752
Position Surface form Disambiguated ID Type / Status
Subject Thalwil E415333 entity
Predicate railConnectionsTo P13914 FINISHED
Object Zug E187177 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: Zug | Statement: [Thalwil, railConnectionsTo, Zug]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zug
Context triple: [Thalwil, railConnectionsTo, 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 (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_69d886d090cc8190a39cb94992586905 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3e80528588190a877dcc6d6d3a392 completed April 18, 2026, 8:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a013a0957c081908a1902aea2f02d2a completed May 11, 2026, 2:08 a.m.
Created at: April 10, 2026, 5:35 a.m.