Triple

T21288661
Position Surface form Disambiguated ID Type / Status
Subject Emscher E524728 entity
Predicate flowsThrough P225 FINISHED
Object Oberhausen E379422 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: Oberhausen | Statement: [Emscher, flowsThrough, Oberhausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oberhausen
Context triple: [Emscher, flowsThrough, Oberhausen]
  • A. Oberhausen chosen
    Oberhausen is an industrial city in Germany’s Ruhr region, historically known for its coal and steel production and heavily affected by World War II bombing.
  • B. Oberhausen
    Oberhausen is a small Bavarian municipality in southern Germany, situated in the rural district of Weilheim-Schongau.
  • C. Oberhausen an der Nahe
    Oberhausen an der Nahe is a small winegrowing village in Germany’s Nahe region, known for its high-quality Riesling vineyards along the Nahe River.
  • D. Remscheid
    Remscheid is a city in North Rhine-Westphalia, Germany, known historically for its metalworking industry and as the birthplace of physicist Wilhelm Röntgen.
  • E. Recklinghausen
    Recklinghausen is a city in the Ruhr area of North Rhine-Westphalia, western Germany, known historically for coal mining and its role as a regional administrative center.
  • 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_69e0b5171f6c8190a5d57201ede73811 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e736d882408190a2300327cb73b7f6 completed April 21, 2026, 8:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0a24970ea881908e0d585753357b24 completed May 17, 2026, 8:27 p.m.
Created at: April 16, 2026, 4:03 p.m.