Triple

T12887128
Position Surface form Disambiguated ID Type / Status
Subject Darmstadt-Dieburg E308256 entity
Predicate contains P35 FINISHED
Object Roßdorf
Roßdorf is a municipality in the German state of Hesse, located near the city of Darmstadt.
E1022626 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: Roßdorf | Statement: [Darmstadt-Dieburg, contains, Roßdorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roßdorf
Context triple: [Darmstadt-Dieburg, contains, Roßdorf]
  • A. Wilmersdorf
    Wilmersdorf is a residential district in southwestern Berlin known for its affluent neighborhoods, shopping streets like Kurfürstendamm, and a mix of historic and modern architecture.
  • B. Oranienburger Vorstadt
    Oranienburger Vorstadt is a historic neighborhood in central Berlin, known for its 19th-century urban fabric, cultural sites, and proximity to key political and intellectual centers of the city.
  • C. Schönewalde
    Schönewalde is a town in the state of Brandenburg, Germany, known for hosting a German Air Force base.
  • D. Ludwigsfelde
    Ludwigsfelde is a town in the German state of Brandenburg, located just south of Berlin and known for its industrial history and automotive manufacturing.
  • E. Reinickendorf
    Reinickendorf is a borough in the northwest of Berlin, Germany, known for its mix of residential neighborhoods, industrial areas, and green spaces including parts of Lake Tegel.
  • 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: Roßdorf
Triple: [Darmstadt-Dieburg, contains, Roßdorf]
Generated description
Roßdorf is a municipality in the German state of Hesse, located near the city of Darmstadt.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Roßdorf
Target entity description: Roßdorf is a municipality in the German state of Hesse, located near the city of Darmstadt.
  • A. Wilmersdorf
    Wilmersdorf is a residential district in southwestern Berlin known for its affluent neighborhoods, shopping streets like Kurfürstendamm, and a mix of historic and modern architecture.
  • B. Oranienburger Vorstadt
    Oranienburger Vorstadt is a historic neighborhood in central Berlin, known for its 19th-century urban fabric, cultural sites, and proximity to key political and intellectual centers of the city.
  • C. Schönewalde
    Schönewalde is a town in the state of Brandenburg, Germany, known for hosting a German Air Force base.
  • D. Ludwigsfelde
    Ludwigsfelde is a town in the German state of Brandenburg, located just south of Berlin and known for its industrial history and automotive manufacturing.
  • E. Reinickendorf
    Reinickendorf is a borough in the northwest of Berlin, Germany, known for its mix of residential neighborhoods, industrial areas, and green spaces including parts of Lake Tegel.
  • 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_69d7bdf7c1f0819098102569a8d8cbf5 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9714415c08190aa9944b494a3ddad completed April 10, 2026, 9:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6e262580c8190ad3f1aa77fd0674c completed May 3, 2026, 5:51 a.m.
NEDg Description generation batch_69f6e4774f4881908692c2d57158db4a completed May 3, 2026, 6 a.m.
NED2 Entity disambiguation (via description) batch_69f6e5630a5c8190bc17abac3cc6612e completed May 3, 2026, 6:04 a.m.
Created at: April 9, 2026, 5:39 p.m.