Triple

T16408755
Position Surface form Disambiguated ID Type / Status
Subject Krefeld E398502 entity
Predicate hasDistrict P459 FINISHED
Object Fischeln E191565 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: Fischeln | Statement: [Krefeld, hasDistrict, Fischeln]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fischeln
Context triple: [Krefeld, hasDistrict, Fischeln]
  • A. Fischeln chosen
    Fischeln is a district of the German city of Krefeld in the state of North Rhine-Westphalia.
  • B. Schwarze Elster
    Schwarze Elster is a river in eastern Germany that flows through Saxony, Brandenburg, and Saxony-Anhalt before joining the Elbe.
  • C. Zweiohrküken
    Zweiohrküken is a 2009 German romantic comedy film and sequel to Keinohrhasen, directed by and starring Til Schweiger.
  • D. Flaemmchen
    Flaemmchen is a young, ambitious stenographer and aspiring actress in Vicki Baum’s novel (and its film adaptation) "Grand Hotel," representing the struggles and dreams of working-class women in Weimar-era Berlin.
  • E. Swallow
    Swallow is the Allied reporting name for the Japanese World War II fighter aircraft Kawasaki Ki-61, known for its inline engine and resemblance to contemporary European fighters.
  • 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_69d87f2950248190bc8ad9b9bebdc8c8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32870e44c8190aae7bc6e6022ceb7 completed April 18, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a003c64a05c8190a59e800ce2318052 completed May 10, 2026, 8:05 a.m.
Created at: April 10, 2026, 5:09 a.m.