Triple

T1298305
Position Surface form Disambiguated ID Type / Status
Subject CHF E27703 entity
Predicate currencyOf P245 FINISHED
Object Büsingen am Hochrhein E20788 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: Büsingen am Hochrhein | Statement: [CHF, currencyOf, Büsingen am Hochrhein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Büsingen am Hochrhein
Context triple: [CHF, currencyOf, Büsingen am Hochrhein]
  • A. Büsingen am Hochrhein chosen
    Büsingen am Hochrhein is a unique German exclave entirely surrounded by Switzerland, known for its special legal and economic status within the Swiss customs area.
  • B. Weil am Rhein
    Weil am Rhein is a German town in the state of Baden-Württemberg, located at the tripoint border with France and Switzerland near Basel.
  • C. 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.
  • D. Pratteln
    Pratteln is a municipality in northern Switzerland that serves as a major residential and industrial center in the canton of Basel-Landschaft.
  • E. 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.
  • 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_69a496d6682881909ba658f1c1e0e2b0 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c0f6bc90819094cad5d62550ea19 completed March 1, 2026, 10:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae650fa53c8190a6db9d10c97f9850 completed March 9, 2026, 6:13 a.m.
Created at: March 1, 2026, 7:51 p.m.