Triple

T22530289
Position Surface form Disambiguated ID Type / Status
Subject Roth district E557013 entity
Predicate hasRiver P165 FINISHED
Object Rednitz 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: Rednitz | Statement: [Roth district, hasRiver, Rednitz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rednitz
Context triple: [Roth district, hasRiver, Rednitz]
  • A. Rednitz chosen
    The Rednitz is a river in Bavaria, Germany, that flows through cities such as Fürth and joins with the Pegnitz to form the Regnitz.
  • B. Duttweiler
    Duttweiler is a village and local district (Ortsteil) of Neustadt an der Weinstraße in the Rhineland-Palatinate wine-growing region of Germany.
  • C. Schönauer
    Schönauer are the inhabitants or natives of Schönau im Schwarzwald, a town in the Black Forest region of Germany.
  • D. Marheineke
    Marheineke is a German surname most notably associated with the 19th-century Protestant theologian Philipp Marheineke.
  • E. Zweigelt
    Zweigelt is Austria’s most widely planted red wine grape, known for producing fruit-forward, medium-bodied wines with soft tannins and vibrant cherry flavors.
  • 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_69e11e57483c8190b0887c4f8ff26446 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15ed6734881908abbbee477dfab98 completed April 29, 2026, 1:28 a.m.
Created at: April 16, 2026, 8:51 p.m.