Triple

T13489275
Position Surface form Disambiguated ID Type / Status
Subject S-Bahn line S1 E318589 entity
Predicate via P5680 FINISHED
Object Schönholz
Schönholz is a locality in Berlin, Germany, served by the city’s S-Bahn rapid transit network.
 E1044352 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: Schönholz | Statement: [S-Bahn line S1, via, Schönholz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Schönholz
Context triple: [S-Bahn line S1, via, Schönholz]
  • A. Schönhausen
    Schönhausen is a village in Saxony-Anhalt, Germany, best known as the birthplace of 19th-century statesman Otto von Bismarck.
  • B. Wilhelmsdorf
    Wilhelmsdorf is a village-level subdivision of the town of Usingen in the Hochtaunus district of Hesse, Germany.
  • C. Rahnsdorf
    Rahnsdorf is a lakeside locality in eastern Berlin, Germany, known for its village-like character, forests, and waterfront along the Müggelsee and nearby waterways.
  • D. Luckenwalde
    Luckenwalde is a town in the German state of Brandenburg known for its industrial heritage and historic architecture, including notable factory complexes.
  • E. Schöneberg
    Schöneberg is a district of Berlin, Germany, historically notable as the site of John F. Kennedy’s famous “Ich bin ein Berliner” speech.
  • 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: Schönholz
Triple: [S-Bahn line S1, via, Schönholz]
Generated description
Schönholz is a locality in Berlin, Germany, served by the city’s S-Bahn rapid transit network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Schönholz
Target entity description: Schönholz is a locality in Berlin, Germany, served by the city’s S-Bahn rapid transit network.
  • A. Schönhausen
    Schönhausen is a village in Saxony-Anhalt, Germany, best known as the birthplace of 19th-century statesman Otto von Bismarck.
  • B. Wilhelmsdorf
    Wilhelmsdorf is a village-level subdivision of the town of Usingen in the Hochtaunus district of Hesse, Germany.
  • C. Rahnsdorf
    Rahnsdorf is a lakeside locality in eastern Berlin, Germany, known for its village-like character, forests, and waterfront along the Müggelsee and nearby waterways.
  • D. Luckenwalde
    Luckenwalde is a town in the German state of Brandenburg known for its industrial heritage and historic architecture, including notable factory complexes.
  • E. Schöneberg
    Schöneberg is a district of Berlin, Germany, historically notable as the site of John F. Kennedy’s famous “Ich bin ein Berliner” speech.
  • 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_69d806b6bfec819089222715b2e86c8e completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaf3cbe2081908c6792362c67c8f1 completed April 12, 2026, 2:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75483a6f88190b3815fb8d97e65e4 completed May 3, 2026, 1:58 p.m.
NEDg Description generation batch_69f7555173d08190be887e81c148192e completed May 3, 2026, 2:01 p.m.
NED2 Entity disambiguation (via description) batch_69f75675df788190b4aa562fe0bc1d75 completed May 3, 2026, 2:06 p.m.
Created at: April 9, 2026, 9:43 p.m.