Triple

T9683657
Position Surface form Disambiguated ID Type / Status
Subject Christian Leumann E234349 entity
Predicate residence P75 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: [Christian Leumann, residence, Bern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bern
Context triple: [Christian Leumann, residence, 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_69ca84c99e34819092e5563a7106cfca completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9ccf21a08190a1302b933b9e50be completed April 1, 2026, 10:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69d19f736b988190b963e216a805316d completed April 4, 2026, 11:32 p.m.
Created at: March 30, 2026, 8:16 p.m.