Triple

T10950825
Position Surface form Disambiguated ID Type / Status
Subject Niendorf E258720 entity
Predicate borderedBy P224 FINISHED
Object Schnelsen
Schnelsen is a residential district in the northwestern part of Hamburg, Germany, known for its suburban character and proximity to major transport routes.
 E894688 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: Schnelsen | Statement: [Niendorf, borderedBy, Schnelsen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Schnelsen
Context triple: [Niendorf, borderedBy, Schnelsen]
  • A. Schnaittach
    Schnaittach is a river in Bavaria, Germany, that serves as a tributary of the Pegnitz River.
  • B. Elsenz
    The Elsenz is a river in southwestern Germany that flows through the Kraichgau region before joining the Neckar.
  • C. Brenkhausen
    Brenkhausen is a village and district of the town of Höxter in North Rhine-Westphalia, Germany.
  • D. Sennfeld
    Sennfeld is a municipality in the Schweinfurt district of Bavaria, Germany, known for its traditional Franconian character and proximity to the city of Schweinfurt.
  • E. Bramsche
    Bramsche is a town in Lower Saxony, Germany, known for its location near Osnabrück and its historical textile industry.
  • 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: Schnelsen
Triple: [Niendorf, borderedBy, Schnelsen]
Generated description
Schnelsen is a residential district in the northwestern part of Hamburg, Germany, known for its suburban character and proximity to major transport routes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Schnelsen
Target entity description: Schnelsen is a residential district in the northwestern part of Hamburg, Germany, known for its suburban character and proximity to major transport routes.
  • A. Schnaittach
    Schnaittach is a river in Bavaria, Germany, that serves as a tributary of the Pegnitz River.
  • B. Elsenz
    The Elsenz is a river in southwestern Germany that flows through the Kraichgau region before joining the Neckar.
  • C. Brenkhausen
    Brenkhausen is a village and district of the town of Höxter in North Rhine-Westphalia, Germany.
  • D. Sennfeld
    Sennfeld is a municipality in the Schweinfurt district of Bavaria, Germany, known for its traditional Franconian character and proximity to the city of Schweinfurt.
  • E. Bramsche
    Bramsche is a town in Lower Saxony, Germany, known for its location near Osnabrück and its historical textile industry.
  • 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_69d6aa88500c819097d7032ca578e74f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770fc156c8190826e124c13ce7242 completed April 9, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69e23c57038c819087671177c2ed5633 completed April 17, 2026, 1:57 p.m.
NEDg Description generation batch_69e24543bd2c8190a3c807baa76c30f6 completed April 17, 2026, 2:35 p.m.
NED2 Entity disambiguation (via description) batch_69e25d11ef24819091e730ae2416a058 completed April 17, 2026, 4:17 p.m.
Created at: April 8, 2026, 9:23 p.m.