Triple

T767395
Position Surface form Disambiguated ID Type / Status
Subject Wilhelm Röntgen E16205 entity
Predicate placeOfBirth P1 FINISHED
Object Remscheid
Remscheid is a city in North Rhine-Westphalia, Germany, known historically for its metalworking industry and as the birthplace of physicist Wilhelm Röntgen.
 E272299 NE FINISHED

How this triple was built (4 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: Remscheid | Statement: [Wilhelm Röntgen, placeOfBirth, Remscheid]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Remscheid
Context triple: [Wilhelm Röntgen, placeOfBirth, Remscheid]
  • A. Bergkamen
    Bergkamen is a town in North Rhine-Westphalia, Germany, known for its coal mining heritage and post-war planned urban development.
  • B. 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.
  • C. Gelsenkirchen
    Gelsenkirchen is a city in western Germany known for its strong football culture and modern stadium, Veltins-Arena, home to FC Schalke 04.
  • D. Wuppertal
    Wuppertal is a city in western Germany known for its steep slopes, extensive parks, and the unique suspended monorail Wuppertal Schwebebahn.
  • E. Bochum
    Bochum is a major city in Germany’s Ruhr region known for its industrial heritage, cultural institutions, and large university.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Remscheid
Triple: [Wilhelm Röntgen, placeOfBirth, Remscheid]
Generated description
Remscheid is a city in North Rhine-Westphalia, Germany, known historically for its metalworking industry and as the birthplace of physicist Wilhelm Röntgen.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Remscheid
Target entity description: Remscheid is a city in North Rhine-Westphalia, Germany, known historically for its metalworking industry and as the birthplace of physicist Wilhelm Röntgen.
  • A. Bergkamen
    Bergkamen is a town in North Rhine-Westphalia, Germany, known for its coal mining heritage and post-war planned urban development.
  • B. 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.
  • C. Gelsenkirchen
    Gelsenkirchen is a city in western Germany known for its strong football culture and modern stadium, Veltins-Arena, home to FC Schalke 04.
  • D. Wuppertal
    Wuppertal is a city in western Germany known for its steep slopes, extensive parks, and the unique suspended monorail Wuppertal Schwebebahn.
  • E. Bochum
    Bochum is a major city in Germany’s Ruhr region known for its industrial heritage, cultural institutions, and large university.
  • F. None of above. chosen

Provenance (5 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_69a49369a0848190af883934cee3db4c completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a6a0fee08190bf365d14c007e008 completed March 1, 2026, 8:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69af1f642cf481908028e4947c98e29c completed March 9, 2026, 7:28 p.m.
NEDg Description generation batch_69af1ffa32008190a8c654a2ae4623aa completed March 9, 2026, 7:31 p.m.
NED2 Entity disambiguation (via description) batch_69af20e52660819080efea271eee7b13 completed March 9, 2026, 7:35 p.m.
Created at: March 1, 2026, 7:37 p.m.