Triple

T10215694
Position Surface form Disambiguated ID Type / Status
Subject Havelland E242434 entity
Predicate containsMunicipality P852 FINISHED
Object Wustermark
Wustermark is a municipality in the Havelland district of Brandenburg, Germany, located west of Berlin and known for its mix of rural character and growing residential and commercial areas.
 E925350 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: Wustermark | Statement: [Havelland, containsMunicipality, Wustermark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Wustermark
Context triple: [Havelland, containsMunicipality, Wustermark]
  • A. Leuenberg
    Leuenberg is a village in Switzerland known as the site where major European Protestant churches concluded the Leuenberg Agreement on church fellowship.
  • 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. Winznau
    Winznau is a municipality in the canton of Solothurn in northwestern Switzerland, situated along the Aare River.
  • E. Geiersthal
    Geiersthal is a small municipality in the Bavarian Forest region of southeastern 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: Wustermark
Triple: [Havelland, containsMunicipality, Wustermark]
Generated description
Wustermark is a municipality in the Havelland district of Brandenburg, Germany, located west of Berlin and known for its mix of rural character and growing residential and commercial areas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Wustermark
Target entity description: Wustermark is a municipality in the Havelland district of Brandenburg, Germany, located west of Berlin and known for its mix of rural character and growing residential and commercial areas.
  • A. Leuenberg
    Leuenberg is a village in Switzerland known as the site where major European Protestant churches concluded the Leuenberg Agreement on church fellowship.
  • 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. Winznau
    Winznau is a municipality in the canton of Solothurn in northwestern Switzerland, situated along the Aare River.
  • E. Geiersthal
    Geiersthal is a small municipality in the Bavarian Forest region of southeastern 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_69d381ae26c48190985abd0e25ee5d04 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d3aa2894d0819095704449ecc2db6c completed April 6, 2026, 12:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5d2d717888190b7e455d006d01033 completed April 20, 2026, 7:16 a.m.
NEDg Description generation batch_69e5d615b6a08190b6000339bec4270d completed April 20, 2026, 7:30 a.m.
NED2 Entity disambiguation (via description) batch_69e5d924963c8190bfc55ffeb529a499 completed April 20, 2026, 7:43 a.m.
Created at: April 6, 2026, 11:05 a.m.