Triple

T16189967
Position Surface form Disambiguated ID Type / Status
Subject The Eaglet E392908 entity
Predicate deathPlace P21 FINISHED
Object Vienna, Austrian Empire 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, Austrian Empire | Statement: [The Eaglet, deathPlace, Vienna, Austrian Empire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vienna, Austrian Empire
Context triple: [The Eaglet, deathPlace, Vienna, Austrian Empire]
  • A. Küniglberg, Vienna
    Küniglberg in Vienna is a prominent hilltop area best known as the main broadcasting campus of Austria’s public broadcaster ORF.
  • 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 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. 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_69d87f1e49ac8190a311b54d32990576 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e222d4ab8081909a02e5138b29b83b completed April 17, 2026, 12:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a000ecd897c81908cbea306c9f95da3 completed May 10, 2026, 4:51 a.m.
Created at: April 10, 2026, 5:02 a.m.