Triple

T12158233
Position Surface form Disambiguated ID Type / Status
Subject Wurzen E289633 entity
Predicate hasSubdivision P747 FINISHED
Object Sachsendorf
Sachsendorf is a locality that forms one of the subdivisions of the town of Wurzen in the German state of Saxony.
E979551 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: Sachsendorf | Statement: [Wurzen, hasSubdivision, Sachsendorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sachsendorf
Context triple: [Wurzen, hasSubdivision, Sachsendorf]
  • A. Sierksdorf
    Sierksdorf is a small coastal municipality in northern Germany, known for its Baltic Sea beaches and the Hansa-Park amusement park.
  • B. Suhrendorf
    Suhrendorf is a small coastal village on the German Baltic Sea island of Ummanz, known for its rural charm and proximity to nature and water sports areas.
  • C. Schattdorf
    Schattdorf is a Swiss municipality located in the central Alpine canton of Uri.
  • D. Hägendorf
    Hägendorf is a municipality in the canton of Solothurn in northwestern Switzerland, known for its residential character and proximity to the Jura mountains.
  • E. Friesdorf
    Friesdorf is a residential subdistrict of the Bonn borough Bad Godesberg in western 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: Sachsendorf
Triple: [Wurzen, hasSubdivision, Sachsendorf]
Generated description
Sachsendorf is a locality that forms one of the subdivisions of the town of Wurzen in the German state of Saxony.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sachsendorf
Target entity description: Sachsendorf is a locality that forms one of the subdivisions of the town of Wurzen in the German state of Saxony.
  • A. Sierksdorf
    Sierksdorf is a small coastal municipality in northern Germany, known for its Baltic Sea beaches and the Hansa-Park amusement park.
  • B. Suhrendorf
    Suhrendorf is a small coastal village on the German Baltic Sea island of Ummanz, known for its rural charm and proximity to nature and water sports areas.
  • C. Schattdorf
    Schattdorf is a Swiss municipality located in the central Alpine canton of Uri.
  • D. Hägendorf
    Hägendorf is a municipality in the canton of Solothurn in northwestern Switzerland, known for its residential character and proximity to the Jura mountains.
  • E. Friesdorf
    Friesdorf is a residential subdistrict of the Bonn borough Bad Godesberg in western 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_69d6ab4c6710819097a9d228382dde43 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915c277e481908351bf4e664dda42 completed April 10, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62a84236c8190baa383c950d2bd62 completed May 2, 2026, 4:47 p.m.
NEDg Description generation batch_69f62e7fc5488190a00dbc8c48db6330 completed May 2, 2026, 5:03 p.m.
NED2 Entity disambiguation (via description) batch_69f62ef4da588190bfe5e418b8f8bf6f completed May 2, 2026, 5:05 p.m.
Created at: April 8, 2026, 9:50 p.m.