Triple

T17010047
Position Surface form Disambiguated ID Type / Status
Subject Euskirchen E412673 entity
Predicate locatedNear P294 FINISHED
Object Zülpich NE NERFINISHED

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: Zülpich | Statement: [Euskirchen, locatedNear, Zülpich]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zülpich
Context triple: [Euskirchen, locatedNear, Zülpich]
  • A. Zülpich chosen
    Zülpich is a historic town in North Rhine-Westphalia, Germany, known for its Roman heritage and medieval fortifications.
  • B. Rüttenscheid
    Rüttenscheid is a lively, upscale district of Essen, Germany, known for its bustling shopping streets, restaurants, and cultural venues.
  • 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. Bergkamen
    Bergkamen is a town in North Rhine-Westphalia, Germany, known for its coal mining heritage and post-war planned urban development.
  • E. Burscheid
    Burscheid is a small town in North Rhine-Westphalia, Germany, known for its location in the hilly Bergisches Land region and its mix of rural character and local industry.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d47a8444819081f1262eb7dbda40 completed April 18, 2026, 6:59 p.m.
Created at: April 10, 2026, 5:33 a.m.