Triple

T21615961
Position Surface form Disambiguated ID Type / Status
Subject Zeulenroda-Triebes E533436 entity
Predicate hasNamePart P5298 FINISHED
Object Zeulenroda
Zeulenroda is a town in the Thuringia region of Germany, known for its scenic reservoir and role as a local administrative and economic center.
E1536709 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: Zeulenroda | Statement: [Zeulenroda-Triebes, hasNamePart, Zeulenroda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zeulenroda
Context triple: [Zeulenroda-Triebes, hasNamePart, Zeulenroda]
  • A. Sonnewalde
    Sonnewalde is a small town in the state of Brandenburg in eastern Germany, known for its rural character and historic architecture.
  • B. Radeberg
    Radeberg is a small town in the German state of Saxony, known for its Radeberger Pilsner brewery and historic town center near Dresden.
  • C. Radeburg
    Radeburg is a small town in the German state of Saxony, situated north of Dresden and known for its historic center and surrounding rural landscape.
  • D. Riederau
    Riederau is a small lakeside district of Dießen am Ammersee in Bavaria, Germany, known for its scenic location on the shores of Lake Ammersee.
  • E. Radebeul
    Radebeul is a town in the German state of Saxony, known for its wine-growing tradition and association with the writer Karl May.
  • 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: Zeulenroda
Triple: [Zeulenroda-Triebes, hasNamePart, Zeulenroda]
Generated description
Zeulenroda is a town in the Thuringia region of Germany, known for its scenic reservoir and role as a local administrative and economic center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Zeulenroda
Target entity description: Zeulenroda is a town in the Thuringia region of Germany, known for its scenic reservoir and role as a local administrative and economic center.
  • A. Sonnewalde
    Sonnewalde is a small town in the state of Brandenburg in eastern Germany, known for its rural character and historic architecture.
  • B. Radeberg
    Radeberg is a small town in the German state of Saxony, known for its Radeberger Pilsner brewery and historic town center near Dresden.
  • C. Radeburg
    Radeburg is a small town in the German state of Saxony, situated north of Dresden and known for its historic center and surrounding rural landscape.
  • D. Riederau
    Riederau is a small lakeside district of Dießen am Ammersee in Bavaria, Germany, known for its scenic location on the shores of Lake Ammersee.
  • E. Radebeul
    Radebeul is a town in the German state of Saxony, known for its wine-growing tradition and association with the writer Karl May.
  • 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_69e0c46411108190bba0d4176dffc9f3 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef3baab9e88190bc02f27133ef32d6 completed April 27, 2026, 10:34 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b0c554fac81908e6159bba70e310e completed May 18, 2026, 12:55 p.m.
NEDg Description generation batch_6a0b0cfa58cc819085e976bf76fbf149 completed May 18, 2026, 12:58 p.m.
NED2 Entity disambiguation (via description) batch_6a0b0d534f1481908e74f754426d321f completed May 18, 2026, 1 p.m.
Created at: April 16, 2026, 6:33 p.m.