Triple

T80003
Position Surface form Disambiguated ID Type / Status
Subject Swiss Patent Office in Bern E1606 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: [Swiss Patent Office in Bern, city, Bern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bern
Context triple: [Swiss Patent Office in 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. Rochester
    Rochester is a major city in western New York State known historically for its role in industry, photography, and social reform movements.
  • C. Burlington
    Burlington is a suburban town in Massachusetts known for its proximity to Boston and its mix of residential neighborhoods, office parks, and retail centers.
  • D. Quincy
    Quincy is a coastal city in eastern Massachusetts known as the "City of Presidents" for being the birthplace of U.S. presidents John Adams and John Quincy Adams.
  • E. Belmont
    Belmont is a suburban town in Middlesex County, Massachusetts, known for its residential character and proximity to Boston.
  • 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_69a24c60d19c8190a1b6c105ca59ef5b completed Feb. 28, 2026, 2:01 a.m.
NER Named-entity recognition batch_69a24f335b5c8190bf2158d884890ac2 completed Feb. 28, 2026, 2:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69a32f24e3888190b99dd0eb4b18db4a completed Feb. 28, 2026, 6:08 p.m.
Created at: Feb. 28, 2026, 2:06 a.m.