Triple

T13063638
Position Surface form Disambiguated ID Type / Status
Subject Norderstedt E329259 entity
Predicate formedByMergerOf P77 FINISHED
Object Harksheide
Harksheide was a former municipality in Schleswig-Holstein, Germany, that later became part of the city of Norderstedt.
 E1017485 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: Harksheide | Statement: [Norderstedt, formedByMergerOf, Harksheide]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Harksheide
Context triple: [Norderstedt, formedByMergerOf, Harksheide]
  • A. Heerdt
    Heerdt is a district of Düsseldorf, Germany, located on the left bank of the Rhine and characterized by a mix of residential, commercial, and industrial areas.
  • B. Reeshof
    Reeshof is a large residential district in the western part of Tilburg in the Netherlands, known for its modern housing developments and green spaces.
  • C. Greifelt
    Greifelt is a German surname most notably associated with Ulrich Greifelt, a high-ranking official in Nazi Germany.
  • D. Kortenberg
    Kortenberg is a municipality in the Flemish Brabant province of Belgium, located between Brussels and Leuven and known for its residential character and green surroundings.
  • E. Boxbergheide
    Boxbergheide is a residential district of the city of Genk in the Belgian province of Limburg.
  • 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: Harksheide
Triple: [Norderstedt, formedByMergerOf, Harksheide]
Generated description
Harksheide was a former municipality in Schleswig-Holstein, Germany, that later became part of the city of Norderstedt.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Harksheide
Target entity description: Harksheide was a former municipality in Schleswig-Holstein, Germany, that later became part of the city of Norderstedt.
  • A. Heerdt
    Heerdt is a district of Düsseldorf, Germany, located on the left bank of the Rhine and characterized by a mix of residential, commercial, and industrial areas.
  • B. Reeshof
    Reeshof is a large residential district in the western part of Tilburg in the Netherlands, known for its modern housing developments and green spaces.
  • C. Greifelt
    Greifelt is a German surname most notably associated with Ulrich Greifelt, a high-ranking official in Nazi Germany.
  • D. Kortenberg
    Kortenberg is a municipality in the Flemish Brabant province of Belgium, located between Brussels and Leuven and known for its residential character and green surroundings.
  • E. Boxbergheide
    Boxbergheide is a residential district of the city of Genk in the Belgian province of Limburg.
  • 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_69d80771749c81909a6d9197b9504872 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d980e9bdfc81908eb90fb50597df64 completed April 10, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbe45c8c819080fbdf1d94376feb completed May 3, 2026, 4:15 a.m.
NEDg Description generation batch_69f6cd3d5090819091b65f544ad139fd completed May 3, 2026, 4:21 a.m.
NED2 Entity disambiguation (via description) batch_69f6cdc8d52c819083717a455d589646 completed May 3, 2026, 4:23 a.m.
Created at: April 9, 2026, 8:59 p.m.