Triple

T12420585
Position Surface form Disambiguated ID Type / Status
Subject Leverkusen E296756 entity
Predicate hasRiver P165 FINISHED
Object Wupper E364898 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: Wupper | Statement: [Leverkusen, hasRiver, Wupper]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wupper
Context triple: [Leverkusen, hasRiver, Wupper]
  • A. Wupper chosen
    The Wupper is a river in North Rhine-Westphalia, Germany, known for flowing through the industrial city of Wuppertal and its surrounding region.
  • B. Blies
    The Blies is a river in western Germany and northeastern France that flows through the Saarland region before joining the Saar River.
  • C. Regnitz
    The Regnitz is a river in the German state of Bavaria that flows through cities such as Erlangen and Bamberg before joining the Main River.
  • D. Schwalm River
    The Schwalm River is a waterway in the German state of Hesse that lends its name to the surrounding Schwalm-Eder region.
  • E. Lippe
    Lippe is a historical region in northwestern Germany that once formed a small principality and later a Free State within the German Reich.
  • 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_69d6ada0640c81908c061d7fb3d47786 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d6efd748190a5d9396a343e41e1 completed April 10, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75464d85c8190a4c27f22cfd7dc96 completed May 3, 2026, 1:57 p.m.
Created at: April 8, 2026, 9:55 p.m.