Triple

T10943664
Position Surface form Disambiguated ID Type / Status
Subject Regionalverband Ruhr E258538 entity
Predicate hasMember P10 FINISHED
Object City of 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: City of Oberhausen | Statement: [Regionalverband Ruhr, hasMember, City of Oberhausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Oberhausen
Context triple: [Regionalverband Ruhr, hasMember, City of 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. City of Essen
    The City of Essen is a major urban center in Germany’s Ruhr area, historically significant as a medieval ecclesiastical seat and later as an important industrial and coal-mining hub.
  • D. 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.
  • E. Elberfeld
    Elberfeld is a historic district of the German city of Wuppertal in North Rhine-Westphalia, known for its 19th-century architecture and early industrial development.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770c3fb388190a598f89ae59a7b51 completed April 9, 2026, 9:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69e4418e52f8819096c75e6e866fecef completed April 19, 2026, 2:44 a.m.
Created at: April 8, 2026, 9:23 p.m.