Triple

T7776838
Position Surface form Disambiguated ID Type / Status
Subject Berchtesgadener Land district E221414 entity
Predicate contains P35 FINISHED
Object Teisendorf
Teisendorf is a market town in southeastern Bavaria, Germany, known for its rural Alpine setting and traditional Bavarian character.
 E693076 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: Teisendorf | Statement: [Berchtesgadener Land district, contains, Teisendorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Teisendorf
Context triple: [Berchtesgadener Land district, contains, Teisendorf]
  • A. Biendorf
    Biendorf is a small municipality in northern Germany notable as the birthplace of German Field Marshal Helmuth von Moltke the Younger.
  • B. Heinersdorf
    Heinersdorf is a residential locality in the borough of Pankow in Berlin, Germany, known for its suburban character and proximity to the city center.
  • C. Hubersdorf
    Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
  • D. Ebersdorf
    Ebersdorf is a historic town in present-day Germany that once served as the capital of one of the small Reuss principalities.
  • E. Ruppersdorf
    Ruppersdorf is a small locality in Germany, historically part of East Prussia, known as the birthplace of German general Otto Lasch.
  • 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: Teisendorf
Triple: [Berchtesgadener Land district, contains, Teisendorf]
Generated description
Teisendorf is a market town in southeastern Bavaria, Germany, known for its rural Alpine setting and traditional Bavarian character.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Teisendorf
Target entity description: Teisendorf is a market town in southeastern Bavaria, Germany, known for its rural Alpine setting and traditional Bavarian character.
  • A. Biendorf
    Biendorf is a small municipality in northern Germany notable as the birthplace of German Field Marshal Helmuth von Moltke the Younger.
  • B. Heinersdorf
    Heinersdorf is a residential locality in the borough of Pankow in Berlin, Germany, known for its suburban character and proximity to the city center.
  • C. Hubersdorf
    Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
  • D. Ebersdorf
    Ebersdorf is a historic town in present-day Germany that once served as the capital of one of the small Reuss principalities.
  • E. Ruppersdorf
    Ruppersdorf is a small locality in Germany, historically part of East Prussia, known as the birthplace of German general Otto Lasch.
  • 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_69ca83ebbef881909ac47f789145fef7 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69caa4d22ee081908081b5f5ecdb4d39 completed March 30, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69caf58a86548190b870417692e4b654 completed March 30, 2026, 10:13 p.m.
NEDg Description generation batch_69caf81d934881908fa41ebd43f3b2e2 completed March 30, 2026, 10:24 p.m.
NED2 Entity disambiguation (via description) batch_69caf9f86d808190880f7bb2fc8d4fe3 completed March 30, 2026, 10:32 p.m.
Created at: March 30, 2026, 4:11 p.m.