Triple

T10711670
Position Surface form Disambiguated ID Type / Status
Subject Höxter E252551 entity
Predicate hasSubdivision P747 FINISHED
Object Ottbergen
Ottbergen is a village and district of the town of Höxter in North Rhine-Westphalia, Germany.
E882437 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: Ottbergen | Statement: [Höxter, hasSubdivision, Ottbergen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ottbergen
Context triple: [Höxter, hasSubdivision, Ottbergen]
  • A. Ortenburg
    Ortenburg is a market town in Lower Bavaria, Germany, known for its historic castle and role as a former seat of the Counts of Ortenburg.
  • B. Haslach
    Haslach is a district or locality that forms part of the town of Oberkirch in the German state of Baden-Württemberg.
  • C. Haslach
    Haslach is a town in southern Germany historically noted as the site of the Battle of Haslach-Jungingen during the Napoleonic Wars.
  • D. Obergoms
    Obergoms is a municipality in the canton of Valais in southwestern Switzerland, known for its high Alpine landscapes and traditional mountain villages.
  • E. Landensberg
    Landensberg is a small municipality in the Bavarian region of southern Germany.
  • 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: Ottbergen
Triple: [Höxter, hasSubdivision, Ottbergen]
Generated description
Ottbergen is a village and district of the town of Höxter in North Rhine-Westphalia, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ottbergen
Target entity description: Ottbergen is a village and district of the town of Höxter in North Rhine-Westphalia, Germany.
  • A. Ortenburg
    Ortenburg is a market town in Lower Bavaria, Germany, known for its historic castle and role as a former seat of the Counts of Ortenburg.
  • B. Haslach
    Haslach is a district or locality that forms part of the town of Oberkirch in the German state of Baden-Württemberg.
  • C. Haslach
    Haslach is a town in southern Germany historically noted as the site of the Battle of Haslach-Jungingen during the Napoleonic Wars.
  • D. Obergoms
    Obergoms is a municipality in the canton of Valais in southwestern Switzerland, known for its high Alpine landscapes and traditional mountain villages.
  • E. Landensberg
    Landensberg is a small municipality in the Bavarian region of southern Germany.
  • 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_69d6aa5cbabc8190973e683950d89faf completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fe523de08190a82c8f057fe8baf6 completed April 9, 2026, 1:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69dbd9cef8a48190a0ec4a27d5702e73 completed April 12, 2026, 5:43 p.m.
NEDg Description generation batch_69dcad07b51081908fd66ee9ff7341f6 completed April 13, 2026, 8:44 a.m.
NED2 Entity disambiguation (via description) batch_69dd4386e3308190bb8503ce75fa628f completed April 13, 2026, 7:27 p.m.
Created at: April 8, 2026, 9:13 p.m.