Triple

T3336721
Position Surface form Disambiguated ID Type / Status
Subject German-speaking Switzerland E70155 entity
Predicate includesCanton P5501 FINISHED
Object Schwyz E282362 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: Schwyz | Statement: [German-speaking Switzerland, includesCanton, Schwyz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schwyz
Context triple: [German-speaking Switzerland, includesCanton, Schwyz]
  • A. Schwyz chosen
    Schwyz is a historic canton in central Switzerland, known as one of the founding members that gave the Swiss Confederation its name.
  • B. Schaffhausen
    Schaffhausen is a historic town and capital of the canton of the same name in northern Switzerland, known for its well-preserved medieval old town and proximity to the Rhine Falls.
  • C. Solothurn
    Solothurn is a canton in northwestern Switzerland known for its historic baroque town of the same name and its location along the Aare River.
  • D. Richterswil
    Richterswil is a picturesque municipality on the shores of Lake Zurich in the canton of Zurich, Switzerland.
  • E. Grenchen
    Grenchen is a Swiss town in the canton of Solothurn known for its watchmaking industry and location at the foot of the Jura Mountains.
  • 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_69ad85a24f208190bcf83131bfed3521 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb1bad97481909359e914d44a1a74 completed March 8, 2026, 5:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5f580e2488190bce70398502e11d4 completed March 14, 2026, 11:55 p.m.
Created at: March 8, 2026, 3:12 p.m.