Triple

T15968910
Position Surface form Disambiguated ID Type / Status
Subject Löhne E387268 entity
Predicate subdivision P747 FINISHED
Object Obernbeck
Obernbeck is a district of the town of Löhne in the Herford district of North Rhine-Westphalia, Germany.
E1186068 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: Obernbeck | Statement: [Löhne, subdivision, Obernbeck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Obernbeck
Context triple: [Löhne, subdivision, Obernbeck]
  • A. Brenkhausen
    Brenkhausen is a village and district of the town of Höxter in North Rhine-Westphalia, Germany.
  • B. Oberthulba
    Oberthulba is a small municipality in northern Bavaria, Germany, known for its rural character and location within the Franconian Saale region.
  • C. Haselbach
    Haselbach is a small municipality in the Straubing-Bogen district of Lower Bavaria in southeastern Germany.
  • D. Beyenburg
    Beyenburg is a historic district in the eastern part of Wuppertal, Germany, known for its medieval monastery, reservoir, and well-preserved village character.
  • E. Boosbeck
    Boosbeck is a village in North Yorkshire, England, situated within the borough of Redcar and Cleveland.
  • 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: Obernbeck
Triple: [Löhne, subdivision, Obernbeck]
Generated description
Obernbeck is a district of the town of Löhne in the Herford district of North Rhine-Westphalia, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Obernbeck
Target entity description: Obernbeck is a district of the town of Löhne in the Herford district of North Rhine-Westphalia, Germany.
  • A. Brenkhausen
    Brenkhausen is a village and district of the town of Höxter in North Rhine-Westphalia, Germany.
  • B. Oberthulba
    Oberthulba is a small municipality in northern Bavaria, Germany, known for its rural character and location within the Franconian Saale region.
  • C. Haselbach
    Haselbach is a small municipality in the Straubing-Bogen district of Lower Bavaria in southeastern Germany.
  • D. Beyenburg
    Beyenburg is a historic district in the eastern part of Wuppertal, Germany, known for its medieval monastery, reservoir, and well-preserved village character.
  • E. Boosbeck
    Boosbeck is a village in North Yorkshire, England, situated within the borough of Redcar and Cleveland.
  • 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_69d86da94ccc819083d187f5dc6a123e completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1572847f08190830e30125e829766 completed April 16, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffbe88fa308190942d37cf67458396 completed May 9, 2026, 11:08 p.m.
NEDg Description generation batch_69ffbf3e80b08190899262a9d03c0e93 completed May 9, 2026, 11:11 p.m.
NED2 Entity disambiguation (via description) batch_69ffbfc0d1548190b7d2e9e10e837f0b completed May 9, 2026, 11:14 p.m.
Created at: April 10, 2026, 4:54 a.m.