Triple

T6936525
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Theology, University of Bern E160565 entity
Predicate city P40 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: [Faculty of Theology, University of Bern, city, Bern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bern
Context triple: [Faculty of Theology, University of Bern, city, 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 a historic waterfront neighborhood in southeast Baltimore, Maryland, known for its revitalized harborfront, rowhouses, and vibrant bar and restaurant scene.
  • D. Canton
    Canton is the historical Western name for Guangzhou, a major port city in southern China and the capital of Guangdong province.
  • 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_69c6884e15208190b9e91487eaafcf85 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6da5eacd8819083252aa1a42d2a5d completed March 27, 2026, 7:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69c75861cd548190a215d616b68101d9 completed March 28, 2026, 4:26 a.m.
Created at: March 27, 2026, 2:27 p.m.