Triple

T8740435
Position Surface form Disambiguated ID Type / Status
Subject Federal Chancellery of Switzerland E207485 entity
Predicate headquartersCity P62 FINISHED
Object Bern E18380 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: Bern | Statement: [Federal Chancellery of Switzerland, headquartersCity, Bern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bern
Context triple: [Federal Chancellery of Switzerland, headquartersCity, Bern]
  • A. Bern chosen
    Bern is the capital city of Switzerland, known for its well-preserved medieval old town and role as a political and cultural center.
  • B. Bron
    Bron is a suburban commune in eastern France that forms part of the metropolitan area of Lyon.
  • C. Canton
    Canton is the historical Western name for Guangzhou, a major port city in southern China and the capital of Guangdong province.
  • D. Canton
    Canton is a historic waterfront neighborhood in southeast Baltimore, Maryland, known for its revitalized harborfront, rowhouses, and vibrant bar and restaurant scene.
  • E. Canton
    Canton is a suburban town in Norfolk County, Massachusetts, located southwest of Boston and known for its residential character and local historic sites.
  • 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_69ca835a03a081909d4d4cd01a18c9fb completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d4a0cf481909c770cb39fd00fcd completed March 31, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf42e7176c819097e313ed8e8ceb06 completed April 3, 2026, 4:32 a.m.
Created at: March 30, 2026, 6:38 p.m.