Triple

T18883533
Position Surface form Disambiguated ID Type / Status
Subject Langenfeld (Rheinland) E461893 entity
Predicate locatedNear P294 FINISHED
Object Solingen 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: Solingen | Statement: [Langenfeld (Rheinland), locatedNear, Solingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Solingen
Context triple: [Langenfeld (Rheinland), locatedNear, Solingen]
  • A. Solingen chosen
    Solingen is a city in western Germany renowned for its centuries-old blade-making tradition and production of high-quality knives and swords.
  • B. Remscheid
    Remscheid is a city in North Rhine-Westphalia, Germany, known historically for its metalworking industry and as the birthplace of physicist Wilhelm Röntgen.
  • C. Bergkamen
    Bergkamen is a town in North Rhine-Westphalia, Germany, known for its coal mining heritage and post-war planned urban development.
  • D. Nettetal
    Nettetal is a town in western Germany’s North Rhine-Westphalia, known for its lakes and nature reserves near the Dutch border.
  • E. Rüttenscheid
    Rüttenscheid is a lively, upscale district of Essen, Germany, known for its bustling shopping streets, restaurants, and cultural venues.
  • 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_69d8dcfc3430819095ee6fc0eb4c06a5 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c3d3dcec8190a468162c6a4482f6 completed April 20, 2026, 6:12 a.m.
Created at: April 10, 2026, 11:57 a.m.