Triple

T18846895
Position Surface form Disambiguated ID Type / Status
Subject Amt Hohe Elbgeest E460939 entity
Predicate hasMunicipality P847 FINISHED
Object Dassendorf
Dassendorf is a small municipality in northern Germany’s Schleswig-Holstein region, situated near the Elbe River and administratively part of the Amt Hohe Elbgeest.
E1345335 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: Dassendorf | Statement: [Amt Hohe Elbgeest, hasMunicipality, Dassendorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dassendorf
Context triple: [Amt Hohe Elbgeest, hasMunicipality, Dassendorf]
  • A. Burkhardtsdorf
    Burkhardtsdorf is a small municipality in the Erzgebirge (Ore Mountains) region of Saxony, eastern Germany.
  • B. Baldramsdorf
    Baldramsdorf is a municipality in the Austrian state of Carinthia, known for its Alpine setting near the town of Spittal an der Drau.
  • C. Stederdorf
    Stederdorf is a district of the town of Peine in Lower Saxony, Germany, known for its residential character and proximity to the regional industrial and agricultural areas.
  • D. Dierdorf
    Dierdorf is a surname most prominently associated with former American football player and sportscaster Dan Dierdorf.
  • 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: Dassendorf
Triple: [Amt Hohe Elbgeest, hasMunicipality, Dassendorf]
Generated description
Dassendorf is a small municipality in northern Germany’s Schleswig-Holstein region, situated near the Elbe River and administratively part of the Amt Hohe Elbgeest.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Dassendorf
Target entity description: Dassendorf is a small municipality in northern Germany’s Schleswig-Holstein region, situated near the Elbe River and administratively part of the Amt Hohe Elbgeest.
  • A. Burkhardtsdorf
    Burkhardtsdorf is a small municipality in the Erzgebirge (Ore Mountains) region of Saxony, eastern Germany.
  • B. Baldramsdorf
    Baldramsdorf is a municipality in the Austrian state of Carinthia, known for its Alpine setting near the town of Spittal an der Drau.
  • C. Stederdorf
    Stederdorf is a district of the town of Peine in Lower Saxony, Germany, known for its residential character and proximity to the regional industrial and agricultural areas.
  • D. Dierdorf
    Dierdorf is a surname most prominently associated with former American football player and sportscaster Dan Dierdorf.
  • 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_69d8dcfa11e4819090ab1ef5bdcd2b2e completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5b8efafdc81909608b8a47deeaa8e completed April 20, 2026, 5:26 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0567743f788190b85a9fa1e7345a27 completed May 14, 2026, 6:11 a.m.
NEDg Description generation batch_6a0568fc78748190b487d4c0b444a8ea completed May 14, 2026, 6:17 a.m.
NED2 Entity disambiguation (via description) batch_6a056966665c81909d9e82f1fbd1d518 completed May 14, 2026, 6:19 a.m.
Created at: April 10, 2026, 11:56 a.m.