Triple

T10943666
Position Surface form Disambiguated ID Type / Status
Subject Regionalverband Ruhr E258538 entity
Predicate hasMember P10 FINISHED
Object City of Bottrop E220286 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 Bottrop | Statement: [Regionalverband Ruhr, hasMember, City of Bottrop]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Bottrop
Context triple: [Regionalverband Ruhr, hasMember, City of Bottrop]
  • A. 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.
  • B. Bottrop chosen
    Bottrop is a city in western Germany’s Ruhr area, historically shaped by coal mining and industry.
  • C. 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.
  • D. Erftstadt
    Erftstadt is a town in the Rhein-Erft district of North Rhine-Westphalia, Germany, located southwest of Cologne and known for its mix of historic villages and suburban residential areas.
  • E. Grevenbroich
    Grevenbroich is a town in North Rhine-Westphalia, Germany, known for its location in the Rhine district of Neuss and its proximity to major industrial and energy-producing regions.
  • 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_69e46283f41c8190ac3e1f196c5e4ca0 completed April 19, 2026, 5:05 a.m.
Created at: April 8, 2026, 9:23 p.m.