Triple

T8439295
Position Surface form Disambiguated ID Type / Status
Subject Rhine-Ruhr metropolitan region E199309 entity
Predicate containsCity P294 FINISHED
Object Recklinghausen E258438 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: Recklinghausen | Statement: [Rhine-Ruhr metropolitan region, containsCity, Recklinghausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Recklinghausen
Context triple: [Rhine-Ruhr metropolitan region, containsCity, Recklinghausen]
  • A. Recklinghausen chosen
    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.
  • B. Gelsenkirchen
    Gelsenkirchen is a city in western Germany known for its strong football culture and modern stadium, Veltins-Arena, home to FC Schalke 04.
  • C. Remscheid
    Remscheid is a city in North Rhine-Westphalia, Germany, known historically for its metalworking industry and as the birthplace of physicist Wilhelm Röntgen.
  • D. Mülheim an der Ruhr
    Mülheim an der Ruhr is a city in western Germany’s Ruhr area, known for its industrial heritage, riverside setting on the Ruhr River, and role as a regional economic and cultural center.
  • E. Oberhausen
    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.
  • 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_69ca8314cd6c8190a6b8c2a1096e18f3 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe13708988190a534e38d8254c9bd completed March 31, 2026, 2:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69d2cae488708190823b1e9c07ad2e48 completed April 5, 2026, 8:49 p.m.
Created at: March 30, 2026, 6:08 p.m.