Triple

T15898946
Position Surface form Disambiguated ID Type / Status
Subject Bautzen district E385533 entity
Predicate containsTown P847 FINISHED
Object Arnsdorf
Arnsdorf is a small municipality in the German state of Saxony, known for its rural character and location near the city of Dresden.
E1225569 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: Arnsdorf | Statement: [Bautzen district, containsTown, Arnsdorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arnsdorf
Context triple: [Bautzen district, containsTown, Arnsdorf]
  • A. Nordendorf
    Nordendorf is a small municipality in Bavaria, Germany, situated within the Augsburg district.
  • B. Aulendorf
    Aulendorf is a small town in the Upper Swabia region of southern Germany, known for its historic castle and spa facilities.
  • C. Allendorf
    Allendorf is a village-level subdivision of the town of Sundern in the Hochsauerland district of North Rhine-Westphalia, Germany.
  • D. Neuendorf
    Neuendorf is a small village on the Baltic Sea island of Hiddensee in Germany, known for its traditional thatched houses and maritime character.
  • E. 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.
  • 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: Arnsdorf
Triple: [Bautzen district, containsTown, Arnsdorf]
Generated description
Arnsdorf is a small municipality in the German state of Saxony, known for its rural character and location near the city of Dresden.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Arnsdorf
Target entity description: Arnsdorf is a small municipality in the German state of Saxony, known for its rural character and location near the city of Dresden.
  • A. Nordendorf
    Nordendorf is a small municipality in Bavaria, Germany, situated within the Augsburg district.
  • B. Aulendorf
    Aulendorf is a small town in the Upper Swabia region of southern Germany, known for its historic castle and spa facilities.
  • C. Allendorf
    Allendorf is a village-level subdivision of the town of Sundern in the Hochsauerland district of North Rhine-Westphalia, Germany.
  • D. Neuendorf
    Neuendorf is a small village on the Baltic Sea island of Hiddensee in Germany, known for its traditional thatched houses and maritime character.
  • E. 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.
  • 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_69d86da5b800819083a31be937d738b0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1563bd0688190b6f7a695be0a4625 completed April 16, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0084a6d6308190ad57a51b380171a2 completed May 10, 2026, 1:14 p.m.
NEDg Description generation batch_6a00851cc9a08190a587bd5951e4d5e0 completed May 10, 2026, 1:16 p.m.
NED2 Entity disambiguation (via description) batch_6a0085e4b6ec81908383085ff08f0dce completed May 10, 2026, 1:19 p.m.
Created at: April 10, 2026, 4:51 a.m.