Triple

T22277698
Position Surface form Disambiguated ID Type / Status
Subject Labe E550648 entity
Predicate tributary P415 FINISHED
Object Schwarze Elster 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: Schwarze Elster | Statement: [Labe, tributary, Schwarze Elster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schwarze Elster
Context triple: [Labe, tributary, Schwarze Elster]
  • A. Schwarze Elster chosen
    Schwarze Elster is a river in eastern Germany that flows through Saxony, Brandenburg, and Saxony-Anhalt before joining the Elbe.
  • B. Fischeln
    Fischeln is a district of the German city of Krefeld in the state of North Rhine-Westphalia.
  • C. Golden Swallow
    Golden Swallow is a classic 1968 Hong Kong wuxia film directed by Chang Cheh and starring Cheng Pei-pei as a skilled female swordswoman.
  • D. Die Adler
    Die Adler is the popular nickname for Eintracht Frankfurt, the German football club known for its eagle emblem and passionate fan base.
  • E. Schwarze Lütschine
    Schwarze Lütschine is a mountain river in the Bernese Oberland region of Switzerland, known for flowing through the Lauterbrunnen Valley before joining the Weisse Lütschine.
  • 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_69e11e44d538819097c6b8f333af3352 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f14ea96948819081c1ae6c7b11ab62 completed April 29, 2026, 12:19 a.m.
Created at: April 16, 2026, 8:40 p.m.