Triple

T22979330
Position Surface form Disambiguated ID Type / Status
Subject Brigittenau E571415 entity
Predicate locatedIn P40 FINISHED
Object Vienna metropolitan area 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: Vienna metropolitan area | Statement: [Brigittenau, locatedIn, Vienna metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vienna metropolitan area
Context triple: [Brigittenau, locatedIn, Vienna metropolitan area]
  • A. Greater Vienna chosen
    Greater Vienna was a historical administrative expansion of Vienna that incorporated surrounding municipalities and districts into a larger metropolitan area, particularly during the Nazi era.
  • B. Vienna
    Vienna is the ancient Roman name for the city of Vienne in southeastern France, which was an important Roman settlement and administrative center in Gaul.
  • C. Vienna
    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 a small town in Dane County, Wisconsin, known for its rural character and proximity to the Madison metropolitan area.
  • E. 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.
  • 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_69e245b3c50481908bb3741ec9f40862 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18293f830819095cca91af7abd742 completed April 29, 2026, 4:01 a.m.
Created at: April 17, 2026, 3:49 p.m.