Triple

T20305352
Position Surface form Disambiguated ID Type / Status
Subject Vöcklabruck District E505595 entity
Predicate containsSettlement P847 FINISHED
Object Schwanenstadt 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: Schwanenstadt | Statement: [Vöcklabruck District, containsSettlement, Schwanenstadt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schwanenstadt
Context triple: [Vöcklabruck District, containsSettlement, Schwanenstadt]
  • A. Schwanenstadt chosen
    Schwanenstadt is a small Austrian town in the state of Upper Austria, known as the birthplace of composer Franz Xaver Süssmayr.
  • B. Dreiflüssestadt
    Dreiflüssestadt is the German nickname for the city of Passau, renowned for its picturesque location at the confluence of the Danube, Inn, and Ilz rivers.
  • C. Käthchenstadt
    Käthchenstadt is a regional nickname for the German city of Heilbronn, referencing the famous play "Das Käthchen von Heilbronn" by Heinrich von Kleist.
  • D. Samt- und Seidenstadt
    Samt- und Seidenstadt is a German nickname for the city of Krefeld, highlighting its historical prominence in the velvet and silk textile industry.
  • E. Dinkelscherben
    Dinkelscherben is a municipality in the Swabian region of Bavaria in southern Germany.
  • 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_69e0b4b8ab648190906e18538c250148 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6773f8f688190b616f972b9bbb28e completed April 20, 2026, 6:58 p.m.
Created at: April 16, 2026, 11:18 a.m.