Triple

T8797479
Position Surface form Disambiguated ID Type / Status
Subject Bad Camberg E209324 entity
Predicate hasPart P35 FINISHED
Object Schwickershausen
Schwickershausen is a village district of the spa town Bad Camberg in the Hesse region of Germany.
E806229 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: Schwickershausen | Statement: [Bad Camberg, hasPart, Schwickershausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schwickershausen
Context triple: [Bad Camberg, hasPart, Schwickershausen]
  • A. Borgholzhausen
    Borgholzhausen is a small town in North Rhine-Westphalia, Germany, known for its location on the Teutoburg Forest and its historical ties to the former County of Ravensberg.
  • B. Schambach
    Schambach is a small river in Bavaria, Germany, that flows into the Altmühl as one of its tributaries.
  • C. Suhl
    Suhl is a city in central Germany known historically as a center of firearms manufacturing and located in the federal state of Thuringia.
  • D. Vellinghausen
    Vellinghausen is a village in western Germany known historically as the site of the Battle of Vellinghausen during the Seven Years' War.
  • E. Korbach
    Korbach is a historic town in the German state of Hesse, known as the district seat of Waldeck-Frankenberg and for its well-preserved medieval old town.
  • 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: Schwickershausen
Triple: [Bad Camberg, hasPart, Schwickershausen]
Generated description
Schwickershausen is a village district of the spa town Bad Camberg in the Hesse region of Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Schwickershausen
Target entity description: Schwickershausen is a village district of the spa town Bad Camberg in the Hesse region of Germany.
  • A. Borgholzhausen
    Borgholzhausen is a small town in North Rhine-Westphalia, Germany, known for its location on the Teutoburg Forest and its historical ties to the former County of Ravensberg.
  • B. Schambach
    Schambach is a small river in Bavaria, Germany, that flows into the Altmühl as one of its tributaries.
  • C. Suhl
    Suhl is a city in central Germany known historically as a center of firearms manufacturing and located in the federal state of Thuringia.
  • D. Vellinghausen
    Vellinghausen is a village in western Germany known historically as the site of the Battle of Vellinghausen during the Seven Years' War.
  • E. Korbach
    Korbach is a historic town in the German state of Hesse, known as the district seat of Waldeck-Frankenberg and for its well-preserved medieval old town.
  • 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_69ca836240888190a62b262e56a69d2f completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5fa370d08190885ef65e3a3e56d3 completed March 31, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69d14bb716cc819096a1e02e61db2e69 completed April 4, 2026, 5:34 p.m.
NEDg Description generation batch_69d14f8eb6b08190b90d1b709f562d4e completed April 4, 2026, 5:51 p.m.
NED2 Entity disambiguation (via description) batch_69d14fde5acc81909555bde89db8f451 completed April 4, 2026, 5:52 p.m.
Created at: March 30, 2026, 6:44 p.m.