Triple

T10587227
Position Surface form Disambiguated ID Type / Status
Subject Kulmbach district E249884 entity
Predicate hasMunicipality P847 FINISHED
Object Harsdorf
Harsdorf is a small municipality in the Bavarian region of Germany, known for its rural character and location within the Upper Franconia area.
E904842 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: Harsdorf | Statement: [Kulmbach district, hasMunicipality, Harsdorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harsdorf
Context triple: [Kulmbach district, hasMunicipality, Harsdorf]
  • A. Hubersdorf
    Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
  • B. Perasdorf
    Perasdorf is a small municipality in the Straubing-Bogen district of Lower Bavaria, Germany.
  • C. Ebersdorf
    Ebersdorf is a historic town in present-day Germany that once served as the capital of one of the small Reuss principalities.
  • D. Teisendorf
    Teisendorf is a market town in southeastern Bavaria, Germany, known for its rural Alpine setting and traditional Bavarian character.
  • E. Tattendorf
    Tattendorf is a small wine-growing village and municipality in Lower Austria, known for its vineyards and rural character.
  • 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: Harsdorf
Triple: [Kulmbach district, hasMunicipality, Harsdorf]
Generated description
Harsdorf is a small municipality in the Bavarian region of Germany, known for its rural character and location within the Upper Franconia area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Harsdorf
Target entity description: Harsdorf is a small municipality in the Bavarian region of Germany, known for its rural character and location within the Upper Franconia area.
  • A. Hubersdorf
    Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
  • B. Perasdorf
    Perasdorf is a small municipality in the Straubing-Bogen district of Lower Bavaria, Germany.
  • C. Ebersdorf
    Ebersdorf is a historic town in present-day Germany that once served as the capital of one of the small Reuss principalities.
  • D. Teisendorf
    Teisendorf is a market town in southeastern Bavaria, Germany, known for its rural Alpine setting and traditional Bavarian character.
  • E. Tattendorf
    Tattendorf is a small wine-growing village and municipality in Lower Austria, known for its vineyards and rural character.
  • 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_69d381c9d3d48190a29ee491e1696a0e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d5276b0ae48190b2935230363239e0 completed April 7, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3e6afdf0c8190924cb14512a89ee8 completed April 18, 2026, 8:16 p.m.
NEDg Description generation batch_69e3f01f9d048190b553184f0f6ce29c completed April 18, 2026, 8:57 p.m.
NED2 Entity disambiguation (via description) batch_69e3f3fef9308190b0354ed436c32e4c completed April 18, 2026, 9:13 p.m.
Created at: April 6, 2026, 12:39 p.m.