Triple

T11360069
Position Surface form Disambiguated ID Type / Status
Subject Buchholz in der Nordheide E269061 entity
Predicate hasNeighbouringCity P3883 FINISHED
Object Jesteburg
Jesteburg is a small municipality in Lower Saxony, Germany, known for its scenic location in the Nordheide region and its residential, village-like character.
E920992 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: Jesteburg | Statement: [Buchholz in der Nordheide, hasNeighbouringCity, Jesteburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jesteburg
Context triple: [Buchholz in der Nordheide, hasNeighbouringCity, Jesteburg]
  • A. Burgstädt
    Burgstädt is a small town in the German state of Saxony, known for its traditional architecture and location near the city of Chemnitz.
  • B. Judenburg
    Judenburg is a historic town in the Austrian state of Styria, known for its medieval architecture and former role as an important trading center.
  • C. Neidenburg
    Neidenburg is the former German name for the town of Nidzica in northern Poland, historically part of East Prussia.
  • D. Osterburg
    Osterburg is a small town in the German state of Saxony-Anhalt, known for its historic architecture and rural surroundings.
  • E. Trostberg
    Trostberg is a small Bavarian town in southeastern Germany known for its historic old town and chemical industry.
  • 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: Jesteburg
Triple: [Buchholz in der Nordheide, hasNeighbouringCity, Jesteburg]
Generated description
Jesteburg is a small municipality in Lower Saxony, Germany, known for its scenic location in the Nordheide region and its residential, village-like character.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jesteburg
Target entity description: Jesteburg is a small municipality in Lower Saxony, Germany, known for its scenic location in the Nordheide region and its residential, village-like character.
  • A. Burgstädt
    Burgstädt is a small town in the German state of Saxony, known for its traditional architecture and location near the city of Chemnitz.
  • B. Judenburg
    Judenburg is a historic town in the Austrian state of Styria, known for its medieval architecture and former role as an important trading center.
  • C. Neidenburg
    Neidenburg is the former German name for the town of Nidzica in northern Poland, historically part of East Prussia.
  • D. Osterburg
    Osterburg is a small town in the German state of Saxony-Anhalt, known for its historic architecture and rural surroundings.
  • E. Trostberg
    Trostberg is a small Bavarian town in southeastern Germany known for its historic old town and chemical industry.
  • 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_69d6aacbe18081909e5fadb50082dd96 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea42fe608190b9c71dd63f8780f3 completed April 9, 2026, 6:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69e543bdd6d88190b4f816ffde5179be completed April 19, 2026, 9:06 p.m.
NEDg Description generation batch_69e5474b77948190b2c45831871383e8 completed April 19, 2026, 9:21 p.m.
NED2 Entity disambiguation (via description) batch_69e54efda820819092d6a94fa4fd21f0 completed April 19, 2026, 9:54 p.m.
Created at: April 8, 2026, 9:33 p.m.