Triple

T9683820
Position Surface form Disambiguated ID Type / Status
Subject Bartholomeus Spranger E234353 entity
Predicate workLocation P7 FINISHED
Object Vienna E7023 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: Vienna | Statement: [Bartholomeus Spranger, workLocation, Vienna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vienna
Context triple: [Bartholomeus Spranger, workLocation, Vienna]
  • A. Vienna chosen
    Vienna is the capital city of Austria, renowned for its rich imperial history, classical music heritage, and vibrant cultural and intellectual life.
  • B. Vienna
    Vienna is a small town in Dane County, Wisconsin, known for its rural character and proximity to the Madison metropolitan area.
  • C. Vienna
    Vienna is the strong-willed saloon owner and central female protagonist in the 1954 Western film "Johnny Guitar."
  • D. Vienna
    Vienna is a suburban town in Fairfax County, Virginia, known for its residential neighborhoods, proximity to Washington, D.C., and access to the Washington Metro via the nearby Vienna/Fairfax–GMU station.
  • E. Wien
    Wien is a German surname most notably borne by physicist Wilhelm Wien, known for his work on blackbody radiation and Wien's displacement law.
  • 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_69d1bcb78e4c8190aaa55de453789168 completed April 5, 2026, 1:36 a.m.
Created at: March 30, 2026, 8:16 p.m.