Triple

T3775494
Position Surface form Disambiguated ID Type / Status
Subject Kaisermühlen E83295 entity
Predicate belongsTo P35 FINISHED
Object federal state of Vienna E279838 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: federal state of Vienna | Statement: [Kaisermühlen, belongsTo, federal state of Vienna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: federal state of Vienna
Context triple: [Kaisermühlen, belongsTo, federal state of Vienna]
  • A. Vienna (state) chosen
    Vienna (state) is Austria’s smallest federal state and its capital city, serving as the country’s political, cultural, and economic center.
  • B. State of Salzburg
    The State of Salzburg is a federal state in western Austria known for its Alpine landscapes, historic baroque capital city of Salzburg, and rich musical heritage associated with Mozart and major cultural festivals.
  • C. Vienna
    Vienna is a small town in Dane County, Wisconsin, known for its rural character and proximity to the Madison metropolitan area.
  • D. Vienna
    Vienna is the capital city of Austria, renowned for its rich imperial history, classical music heritage, and vibrant cultural and intellectual life.
  • 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 (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_69ad8b235e608190b5a2b1d1bfcef50b completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcc5ac9688190bc921cd3ba1d0580 completed March 8, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4e53209888190823412fabacbc914 completed March 14, 2026, 4:33 a.m.
Created at: March 8, 2026, 3:36 p.m.