Triple

T5490131
Position Surface form Disambiguated ID Type / Status
Subject Osnabrück district E123679 entity
Predicate contains P35 FINISHED
Object Kettenkamp
Kettenkamp is a small municipality in Lower Saxony, Germany, situated in the rural Osnabrück region.
 E522574 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: Kettenkamp | Statement: [Osnabrück district, contains, Kettenkamp]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kettenkamp
Context triple: [Osnabrück district, contains, Kettenkamp]
  • A. Kampen
    Kampen is a historic Dutch city known for its well-preserved medieval center and riverside location in the province of Overijssel.
  • B. Karakays
    Karakays are an ethnic community historically associated with the region of Gözleve (modern-day Yevpatoria) in Crimea.
  • C. Rycken
    Rycken is a Dutch-origin surname historically borne by families such as that of Abraham Rycken in the Low Countries and early colonial America.
  • D. Tarpenning
    Tarpenning is the surname of Marc Tarpenning, an American engineer and entrepreneur best known as a co-founder of Tesla Motors.
  • E. Ringen
    Ringen is a station on the Oslo Metro system that serves as a key endpoint for certain metro lines in Norway’s capital.
  • 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: Kettenkamp
Triple: [Osnabrück district, contains, Kettenkamp]
Generated description
Kettenkamp is a small municipality in Lower Saxony, Germany, situated in the rural Osnabrück region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kettenkamp
Target entity description: Kettenkamp is a small municipality in Lower Saxony, Germany, situated in the rural Osnabrück region.
  • A. Kampen
    Kampen is a historic Dutch city known for its well-preserved medieval center and riverside location in the province of Overijssel.
  • B. Karakays
    Karakays are an ethnic community historically associated with the region of Gözleve (modern-day Yevpatoria) in Crimea.
  • C. Rycken
    Rycken is a Dutch-origin surname historically borne by families such as that of Abraham Rycken in the Low Countries and early colonial America.
  • D. Tarpenning
    Tarpenning is the surname of Marc Tarpenning, an American engineer and entrepreneur best known as a co-founder of Tesla Motors.
  • E. Ringen
    Ringen is a station on the Oslo Metro system that serves as a key endpoint for certain metro lines in Norway’s capital.
  • 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_69bd464a2d908190869324ce176779c8 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd927dcb848190a9d31e2435f8a755 completed March 20, 2026, 6:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf48ac6e7881908806f88056409b41 completed March 22, 2026, 1:41 a.m.
NEDg Description generation batch_69bf497a88b48190b87bf175fe224211 completed March 22, 2026, 1:44 a.m.
NED2 Entity disambiguation (via description) batch_69bf4a1f6e1c8190a9ae94e45fb16cf9 completed March 22, 2026, 1:47 a.m.
Created at: March 20, 2026, 2:10 p.m.