Triple

T6735836
Position Surface form Disambiguated ID Type / Status
Subject Hamm E153750 entity
Predicate hasDistricts P1679 FINISHED
Object Bockum-Hövel
Bockum-Hövel is a district in the city of Hamm in North Rhine-Westphalia, Germany, characterized by its mix of residential areas, local industry, and historical roots as a former independent municipality.
 E614930 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: Bockum-Hövel | Statement: [Hamm, hasDistricts, Bockum-Hövel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bockum-Hövel
Context triple: [Hamm, hasDistricts, Bockum-Hövel]
  • A. Bockum
    Bockum is a residential district of the German city of Krefeld, known for its green spaces and affluent neighborhoods.
  • B. Göhren
    Göhren is a seaside resort town on the Baltic Sea coast of Germany, located on the island of Rügen and known for its beaches and tourism.
  • C. Hakenfelde
    Hakenfelde is a locality in the Berlin borough of Spandau, known for its residential areas, green spaces, and proximity to the Havel River.
  • D. Bernlohe
    Bernlohe is a village-level district that forms part of the town of Roth in Bavaria, Germany.
  • E. Rheinhausen
    Rheinhausen is a district of the German city of Duisburg, located on the western bank of the Rhine in North Rhine-Westphalia.
  • 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: Bockum-Hövel
Triple: [Hamm, hasDistricts, Bockum-Hövel]
Generated description
Bockum-Hövel is a district in the city of Hamm in North Rhine-Westphalia, Germany, characterized by its mix of residential areas, local industry, and historical roots as a former independent municipality.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bockum-Hövel
Target entity description: Bockum-Hövel is a district in the city of Hamm in North Rhine-Westphalia, Germany, characterized by its mix of residential areas, local industry, and historical roots as a former independent municipality.
  • A. Bockum
    Bockum is a residential district of the German city of Krefeld, known for its green spaces and affluent neighborhoods.
  • B. Göhren
    Göhren is a seaside resort town on the Baltic Sea coast of Germany, located on the island of Rügen and known for its beaches and tourism.
  • C. Hakenfelde
    Hakenfelde is a locality in the Berlin borough of Spandau, known for its residential areas, green spaces, and proximity to the Havel River.
  • D. Bernlohe
    Bernlohe is a village-level district that forms part of the town of Roth in Bavaria, Germany.
  • E. Rheinhausen
    Rheinhausen is a district of the German city of Duisburg, located on the western bank of the Rhine in North Rhine-Westphalia.
  • 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_69c6880bdd68819097de8b6099992682 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d18369d88190a73349075462202b completed March 27, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69c70b09b97c8190a5a538571b6909f0 completed March 27, 2026, 10:56 p.m.
NEDg Description generation batch_69c70bda97f08190bc6dab7177341876 completed March 27, 2026, 10:59 p.m.
NED2 Entity disambiguation (via description) batch_69c70c51e0148190be64afb56690b34f completed March 27, 2026, 11:01 p.m.
Created at: March 27, 2026, 2:09 p.m.