Triple

T18219612
Position Surface form Disambiguated ID Type / Status
Subject Vienna Volksoper E436257 entity
Predicate ownedBy P347 FINISHED
Object City of Vienna NE NERFINISHED

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: City of Vienna | Statement: [Vienna Volksoper, ownedBy, City of Vienna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Vienna
Context triple: [Vienna Volksoper, ownedBy, City of Vienna]
  • A. Vienna
    Vienna is a small town in Dane County, Wisconsin, known for its rural character and proximity to the Madison metropolitan area.
  • B. 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.
  • C. Vienna chosen
    Vienna is the capital city of Austria, renowned for its rich imperial history, classical music heritage, and vibrant cultural and intellectual life.
  • D. Vienna
    Vienna is the strong-willed saloon owner and central female protagonist in the 1954 Western film "Johnny Guitar."
  • E. Küniglberg, Vienna
    Küniglberg in Vienna is a prominent hilltop area best known as the main broadcasting campus of Austria’s public broadcaster ORF.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9103a8081908bbb0836fef10efd completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4e47a3b1c8190919e954089b41ae0 completed April 19, 2026, 2:19 p.m.
Created at: April 10, 2026, 10:32 a.m.